AE/Fatigue Testing of a Stiffened Wing Skin Panel at Northrup

JOURNAL OF ACOUSTIC EMISSION
Editor: Kanji Ono
Associate Editors: A. G. Beattie, T. F. Drouillard, F. C. Beall and M. Ohtsu
1.

Aims and Scope or the Journal

Journal of Acoustic Emission is an international journal
designed to be of broad interest and use to both researcher andpractitioner of acoustic emission. It will publish original contributions of all aspects of research and significant engineering
advances in the sciences and applications of acoustic emission.
The journal will also publish reviews, the abstracts of papers
presented at meetings, technical notes, communications and summaries of reports. Current news of interest to the acoustic emission communities, announcements of future conferences andworking group meetings and new products will also be included.
Journal of Acoustic Emission includes the following classesof subject matters;
A. Research Articles: Manuscripts should represent completed original work embodying the results of extensive investigation. These will be judged for scientific and technical merit.
B. Applications: Articles must present significant advancesin the engineering applications of acoustic emission. Material
will be subject to reviews for adequate description of procedures,substantial database and objective interpretation.
C. Technical Notes and Communications: These allow publications of short items of current interest, new or improved experimental techniques and procedures, discussion of pUblished articles
and relevant applications.
D. AE Literature section will collect the titles and abstractsof papers published elsewhere and those presented at meetingsand conferences. Reports and programs of conferences andsymposia will also be presented.
Reviews, Tutorial Articles and Special Contributions willaddress the subjects of general interest. Nontechnical part will
cover book reviews, significant personal and technical accomplishments, current news and new products.

2.

Endorsement

Acoustic Emission Working Group (AEWG), European
Working Group on Acoustic Emission (EWGAE). Committee on
Acoustic Emission from Reinforced Composites (CARP), andAcoustic Emission Working Group of India have endorsed the
publication of Journal of Acoustic Emission.

3.

Governing Body

The Editor and Associate Editors will implement the editorial
policies described above. The Editorial Board will advise the editors on any major change. The Editor, Professor Kanji Ono, has
the general responsibility for all the matters. Associate Editors
assist the review processes as lead reviewers. Mr. T.F. Drouillard
is responsible for the AE Literature section. The members of the
Editorial Board are selected for their knuwledge and experience on
AE and will advise and assist the editors on the publication
policies and other aspects. The Board presently includes thefollowing members:

S.H. Carpenter
D.A. Dornfeld
P. Reischmann
L. Golaski
M.A. Hamstad
H.R. Hardy, Jr.
R. Hill
I.V. Ivanov

P. JaxT. Kishia.Y. Kwon
J.c. Lenain
S.L. McBride
W. Morgner
C.R.L. Murthy
H. Niitsuma
A.A. Pollock
T.M. Proctor, Jr.
I. RomanC. Scala
C. ScrubyA. Vary
E. Waschkies
M. Wevers
J.W. Whittaker
B.R.A. Wood

4.

(USA)
(USA)
(France)(Poland)
(USA)
(USA)
(UK)
(Russia)(Germany)(Japan)(Korea)(France)(Canada)(Germany)(India)(Japan)(USA)(USA)(Israel)(Australia)
(UK)
(USA)
(Germany)(Belgium)(USA)(Australia)

Publication

Journal of Acoustic Emission is published quarterly inMarch. June. September and December by Acoustic Emission
Group. 308 Westwood Blvd.- Box 364. Los Angeles. CA 900241647. It may also be reached at 5731 Boelter Hall, University ofCalifornia. Los Angeles, California 90095-1595 (USA). tel. 310825-5233. FAX 818-368-8309. e·mail: ono@seas.ucla.edu
r5.

Subscription

Subscription should be sent to Acoustic Emission Group.
Annual rate for 1995 or 1996 is US $96.00. For surface delivery.
add $8 in the U.S. and $1 I for Canada and elsewhere. For air maildelivery to South America, add S18. Western Europe, add S25 andadd $30 elsewhere. Overseas orders must be paid in US currencies
with a check drawn on a US bank. Inquire for individual (withinstitu-tional order) and bookseller discounts.

6.

Advertisement

No advertisement will be accepted, but announcements forbooks. training courses and future meetings on AE will be
included without charge.

ISSN 0730-0050 Copyright © 1995 Acoustic Emission Group

Coden: JACEDO

Primed in U.S.A.

Early Detection of Damages in Journal Bearings by
Acoustic Emission Monitoring
Dong-Jin Yoon, Oh-Yang Kwon, Min-Hwa Chung and Kyung-Woong Kim
Most industrial plants and machinery have rotationalparts. Among them. bearings are very important since thefailure of a critical bearing may cause a system shutdown.
Therefore the necessity for the development of bearing surveillance method cannot be overemphasized. The role ofearly detection of damages is especially important for journal bearings since they are often used under high speed. hightemperature and heavy load conditions.

Abstract
Journal bearings in rotating machinery are vulnerable tothe contamination or the insufficient supply of lubricant,which is likely to cause the unexpected shutdown or malfunction of the machinery. Various destructive and nondestructive testing methods had been used for the reduction ofmaintenance cost and accidents related to bearing damages.
In this experimental approach, acoustic emission (AE) technique is employed for the detection of incipient failurecaused by the intervention of foreign particles most probable in journal bearings. Experimental schedule was <bsigned to be quantitative and systematic by varying theminimum oil film thickness and the size of alumina panicles added to the lubrication layer. AE rms voltage, waveforms, and distributions of AE parameters are used for the
analysis and characterization of AE sources. The results
showed that the progress of damage was well correlated withthe change of AE rms voltage. The type of AE sources canbe verified using other information such as wavefonns mJ
distribution of events by signal energy.

The current methods of bearing diagnosis generally utilize traditional tools such as the measurement of shaft vibration or displacement, the measurement of oil and bearing
temperature. and the monitoring of oil contamination.
which are conducted as either on-line or periodic inspection(Elwell. 1985; Harting. 1978). However. they are practically useful only after the abnormal condition of structuresdeveloped. In other words. they are incapable of detecting
the incipient failure.
It has been known that acoustic emission is an effective
tool for early detection of damages due to metallic contact orwear action (Kannatey-Asibu and Dornfeld. 1982; Dornfeld.
1992). The purpose of the present study is to investigate
the usefulness and applicability of AE technique for the
early detection of damages in journal bearings caused by theintervention of foreign particles.

1. Introduction
Recent interests for the safe and optimal operation ofindustrial plants with the trend of unmanned operation necessitate the development of on-line monitoring tecturiques.
A number of techniques are currently utilized for diagnosis
and monitoring of various machinery (SalO et a1.. 1983;
Elwell. 1985; Dornfeld, 1992). Nevertheless, numerous
studies are also conducted for developing new and better
techniques (Akagaki and Kato. 1992; Holroyd and Randall,1993).

2. Related Studies
The application of AE technique to the bearing diagnosis was first mentioned by Balderston (1969). In the article
entitled ''The detection of incipient failure in bearings". heclassified the basic sources of noise in bearings to threephenomena, i.e.. the sounds of rotation. resonant frequencies, and acoustic emission. Since then practical studies of
AE technique for bearing diagnosis have been actively conducted. It was reported that AE was superior to the vibration analysis method in the condition monitoring of rolling
element bearings. and that frequency components higher
than 100 kHz. were more effective for the AE technique(Ensor and Fong, 1975). Incipient failure detection (lFD)
technique for bearing diagnosis was also proposed in thesame period. The experimental results using IFD. AB. ~celerometerwere compared with each other (Haning. 1977;
Harting. 1978).

Received I August 1994. DJ. Yoon is affiliated with Center for
Materials Evaluation. Korea Research Institute of Standards andScience. p.a.Box 102. Yusong. Taejon. 305-600. Korea(djyoon@krissol.kriss.re.kr). a.Y. Kwon is with Dept. of Mechanical Engineering. Inha Univ.• Inchon. Korea, M.H. Chungis with Research Center. Korea Electric Power Corp.. Taejon.
Korea, and K.W. Kim is with Dept of Precision Engineeringand Mechatronics. KAIST. Taejon. Korea.

Journal of Acoustic Emission
VolulllC 13. Numbers 1/2

10730-00SOI95ISS.00I13001·13010

Copyrigbt~I99S Acoustic Emission GroupThe usefulness of AE technique was proved for the detection of rolling contact fatigue of rolling element bearings
considering the limitation of vibration analysis (Adachi andShoji, 1981; Yoshioka and Fujiwara, 1982). The usefulness of high frequency resonant technique (HFRT) for thevibration analysis has also been demonstrated (McFadden
and Smith, 1984). It was also suggested that democlulated
AE signal is a useful parameter for the diagnosis of rolling
element bearings (Bagnoli et aI., 1988). It was shown that
defects of various size could be detected using AE techniqueand the peak amplitude appeared to be an effective measure
for condition monitoring of bearings (fandon and Nakra,
1990).

Motor

On the other hand, there are only a few studies of AE
techniques for the journal bearing diagnosis comparing tothose for rolling element bearings. Most of the cmrent
diagnosis schemes for journal bearings are heavily dependent
on the monitoring of lubricating oil; for example, spectr0metric oil analysis program (SOAP), ferrography. magnetic
particle examination. filter analysis, etc. (Akagaki and Kato.
1992) Wear debris in lubricating oil has been analyzed formonitoring of the damages of journal bearings tested to
failure under the lack of lubrication, using SOAP, ferrography, and scanning electron microscopy (SEM) analysis(Akagaki and Kato. 1992). The condition monitoring of
lubrication oil was already emphasized in the report for thesurveillance of turbine bearings (Elwell, 1985). Anotherexperimental work was done to evaluate the wear life ofjournal bearing lubricaaed by contaminated oils. As a results, empirical fonnulas to estimate the wear rates of journal and bearings were obtained as a function of contamination level and operating conditions (Watanabe et al., 1985).
In the study of practical applications of AE technique forjournal bearings diagnosis, the envelope detection and wavefonn parameters of AE signals were used for detecting abnonnal conditions such as metal wipe, tilting, and rubbing
in full-scale journal bearings (Sato et aI., 1983). Although
the contamination of lubricating oil either by wear debris orby foreign particles is known as the major cause of bearing
failures, there has been virtually no study to monitor thecontamination or oil quality using acoustic emission.

(a)

(b)

Fig. I (a) Experimental apparatus for the journal bearing
monitoring. (b) Block diagram for the AE measurement
system.
The journal used for this test was a cylindrical type andis exchangeable since it fits to main shaft with a keyway.
Test bearings were commercial copper-lined kelmet bearings
being used for automobile engines. The sizes are 58 mm
dia. and 49 mm width. The bearing is separated into theupper and lower half. Oil groove is machined circumferentially on the upper half with oil inlet at the center. AE
sensor was attached to the lower half of the bearing using
vacuum grease couplant with proper pressure. AE signals
were detected by a wideband type sensor (model WO. PAC)
with maximum sensitivity of -60 dB (ref. IV/J1bar) at 550
kHz. The sensor output was fIrSt amplified by 60 dB at
preamplifier then fed into an AE signal processing unit,
microprocessor-based AETSSOO, where AE parameters wereextracted. The preamplifier output was also fed into a digital storage oscilloscope and an HP3400A nns volbneter. A
block diagram for the AE measurement system and otherequipment is shown in Fig. 1(b).

3. ExperimeDt
3. J Apparatus and Measurements
Most of wear tests or simulated bearing tests have been
conducted on specialized test rigs which enable simple testpieces to be loaded and rubbed with mating surface. In thisstudy, however, ajoumal bearing was designed to run in thecondition of typical hydrodynamic lubrication in order tocontrol oil film thickness between the bearing and the journal. Experiments were carried out Wider several abnormal
conditions by adding foreign particles to lubricant layer.
Experimental apparatus for journal bearing monitoring is
schematically shown in Fig. l(a).

3.2 Minimum Oil Film Thickness (MOFT)

The infonnation such as the bearing clearance and theminimum oil film thickness is essential for experimentswith the controlled amount and size of foreign particles. In
2experimenrs adding particles or having the metallic contact
between two surfaces, the above infonnation is important inunderstanding the state of lubrication layer. In this study,
calculated experimental parameters were employed to the0retically maintain the same MOFT of IS Jim at different
loads or rotational speeds. The MOFT value was used as a
guideline to choose the size of foreign particles.

Table I Relationship between parameters at 200 rpm.
Iunin (urn)Eccentricity==

923.35983.671052.421131.50
1223.441322.64
1428.83
1566.00
1717.11
1919.122151.102416.672757.04
3209.023838.244774.396117.198156.2513050.00
27964.29

20.0
19.0
18.0
17.0
16.0
. ·;15.0.
14.0
13.0
12.0
11.0
10.0
9.0
8.0
7.0
6.0
5.0
4.0
3.0
2.0
1.0

0.900
0.905
0.910
0.915
0.920
0.925
0.930
0.935
0.940
0.945

Oil film thickness, h, between the journal and the bearing, when bearing cleaIm1ce is C and eccentricity is e, canbe written as follows for the angle of rotation 9.
h C (l + e cos 9).
An unwrapped view ofthickness profile for the circumferential direction of oil film is shown in Fig. 2. Minimum oilfilm thickness, h..n. or MOFT, can be given byh",tft C (I - e)
as it has minimum value when 9 is n.

Load capacity (N)

0.950
0.955
0.960
0.965
0.970
0.975
0.980
0.985
0.990
0.995

Table 2 Summary of overall experimental schedule.
~~

seriesl!::l~~
0.1
1

8~ , , ; , ; , , , r ' , , ,:, ,; : ::: , , > , r ' , , , , , , ; ~
o
I

.e

n

38

~

2. Addition

1. Injection

•

0.01

0.1

0.5

200

0

0

0

-

600

0

0

0

-

200

0

0

0

0

600

0

0

0

-

200

0

0

0

0

600

0

0

-

-

200

0

600

0

0
0

-

-

the normallubrieation layer and the other the lubricant c0ntamination by wear debris or other impurities generaled during prolonged operation. In the latter case, we are interested
in how the degree of contamination of oil, or the concentration of particles in lubricant oil, affect the tendency of bearing damage and AE signals. Therefore, the experiments
were conducted by two methods; one is the injection of particles to oil inlet for a short period and the other is the c0ntinuous circulation of lubricant mixed with particles in oilbath. Experimenrs were conducted under two rotational
speeds of 200 rpm and 600 rpm for each particle size. The
overall experimental plan for the two methods is summarized in Table 2.

Fig. 2 Unwrapped view of oil film thickness.
As an example of the theoretica11y calculated values,
the relationship between MOFf and the required load forrotational speed of 200 rpm at a given eccentricity ratio isshown in Table 1.

3.3 Experimental Conditions
Because the contamination of lubricant by foreign particles is the major cause of bearing failures, we consider two
types of experimental conditions. One is the intervention offoreign particles such as sands, metal chips, wear debris to3

3.3.1 Foreign particles by injection
Abrasive grade alumina(AI10 3) particles of known size
were used to conduct the experiments more systematicallyand quantitatively. Four nominally different sizes of 0.1
Jim, I Jim, 8 Jim, and 38 Jim were employed using the
MOFT value of 15 Jim. While supplying clean oil at therate of 250 ml/min, oil premixed with particles was introduced to the oil inlet using an injector at the rate of about
0.15 mllmin.

60(0) 0.1 pm

40

Beginning ofEnd of.- Injection~Injection

20
0
80

3.3.2 Foreign particles by mixing in oil bath
After mixing particles by using stirrer in the oil tank at
a predetennined concentration, the contaminated oil was
supplied through the oil inlet continuously. For each size
selected above, three different concentrations of 0.01, 0.1,
and 0.5 percent in volume were employed. The concentration is the quantity of mixed particles to the total amount of
oil in the oil bath.

(b) 1 p.m
BegIMlng of.- Injection

60

End of.-Injection

~40
'-'

IJJ

20

C)

~

4. Results and Discussion

:...J

0

~ 60

4./ Effect ofForeign Particles by Injection(c) 8 pm(/)~

Beginning ofa::: 40

4.1.1 Effect of particle size
AE intensity in rms voltage with various size of foreign particles from 0.1 to 38 Jim are shown in Fig. 3.
When 0.1 J.1m particles were introduced, the change in AE
rms voltage level consisted of a series of small spikes asshown in Fig. 3(a). This result was due to the effect ofvery fine particles generating AE signals of small energy
when they pass through the lubricant layer. When the partiele size was increased to 1 or 8 J.LID. the intensity showed aconsiderable increase as shown in Fig. 3(b) and (c). This
indicated that the source of AE energy increased when thesize of particles approached to a fraction of MOFT, and theabnormal condition can be easily detected. Since the overall
AE rms voltage level for I Jim particles appeared higher
than that of 8 Jim particles. the particles size and the stateof powder were in\restigated by SEM observation. It was
found that 1 Jim particles were agglomerated to a size larger
than 8 J.1m and the agglomerated I J.1m particles acted as
particles larger than 8 J.1m. AE intensity increased drastically when the size of particles was larger than the MOFr
as shown in Fig. 3(d). AE rms voltage remained several
times above the background noise long after the injection ofparticle was stopped. This was because a portion of particles larger than MOFT stuck in the lubrication layer andgenerated continuous AE signals with high energy.

End of~ Injection.-Injection

IJJ

<:
20

0
300
Beginning of.- Injection

End of.-Injr:ction(d) 38 pm

240
180
120
60

o

o

2

4

6

8

10

12

TIME (minutes)
Fig. 3 AE intensity with various size of particles injected.
of 38 Jim typically generate continuous AE signals, whichappear to be from continuous abrasive wear sources.

Typical waveforms obtained from the introduction ofparticles are shown in Fig. 4. Particles less than MOFT,
such as 0.1 J.lDl, I J.lrn. and 8 J.1m. generated burst type signals intermittently with different amplitude and energy.

Distributions of AE events by signal energy for eachexperiment are shown in Fig. 5 Generally. the distributions
are similar to each other. The energy distribution shifted to
the right when the large particles were introduced. This also
indicated that the energy of AE signal changed with the sizeof particles. As an additional analysis for clarifying theThis implies that each particle in lubricant layer acts as
an erosive source to the journal or bearing surface. Particles
4

(0)

88

8. I um(a) 0.1 /l m

'l'1I"

He,..

59 ur./d i v

Ua,.

B.3 U/div-Cb) 1 Ual

Ho,..

59 ur./div(b) 1 /l m

Ua,.. : B.3 U/div
(c)

B um

e
Zll 24 Zll 3Z 36 4Il 44 4Il 52 56 68 601 68 72 710 8lI 1M 8lI 9Z 96
DIIt. 1 or DIDIlS II DlEIICY rca _ _-.at or I~ • lIlI
IIIftIlIlIIIL SIIZ • 1

Ho,..

5e u:o/div

Ue,.

B.3 V/divz(e) 8 /lm

488(d) 38 ulll(d) 38 /l m
Ho,. : 58 ur./div

Va,. : B.3 U/div

Fig. 4 Typical wavefonns recorded from each experiment.
effect of particle size on AE intensity, the cross-plot of peak
amplitude vs. event duration was made for each experimentas shown in Fig. 6. With the increase of particle size from
0.1 to 38 J1m, peak amplitude increased about 10 dB at
most. On the other hand, a tremendous increase in event
duration was noticed, which contributed to the higher energy
value of AE signals.

Fig. 5 Distribution of events by energy from each experiment.
face. Watanabe et al. (1985) reported that wear rates increased in proportion to the rotating speed of shaft linearlyin the journal bearing lubricated by contaminated oils. In
addition to the overall increase in AE intensity by increasing rotating speed from 200 to 600 rpm. numerous intermittent spikes were also observed after the end of injection.
It appeared the bearing surface was continuously worn away
by small amount of particles deposited or settled on thesurface due to higher speed. From the observation of bearing surface at the completion of both lower and higher speed
experiments some particles were found from the surface oflower half bearing so that the above assumption was veri-

4.1.2 Effect of rotating speed
Figure 7 reveals very different results of AE rms voltage data in the case of injection of same size particles fordifferent rotating speeds. For the same MOFT value, theeffect of particle injection was sensitive to the increasing
rotating speed. It is expected that the total sliding distancein the higher rotating speed must be longer than that in thelower rotating speed for the same testing time. Therefore
the number of signals or the AE rms voltage level generated
during the same running time increased. With the increaseof speed, the impingement or the friction of particles to thebearing surface generates AS signals with high energy,
which resulted in the severe wear or damage of bearing sur-

fied.
5

70 , - - - - - - - ----..,

70 , - - - - - - - - - - - - - - - - - - - ,(0) 0.1 um Nt03(b) 1 um "'/)s
200 ~200 rpm
130 kgf

130 kgf

o

a

o

."

a
o

•

"

_
00
_OOID

~

...

0

..

• ••• •
ao
•
a

0
00

..

••••••~• • 0

40 1"

"

o

a

•

•

0

100

a

0

_a

a

a

DaD
0

Dame- : : :Ea:==='IZI~aD_IDI--.:D

:a

00

0°.=
a

00..

Da

11:1

.D

-_
__

.........

ODDaa

D CDmI ilia • •

~
.aa_.
..

ID

".0

1m. •

ODD

ODiliaD _lUI 00
....

0

••

D

D

.

a

aa
~

_D

D

1 -_ _--1

4 0 ' - - - - . 1 . - -_ _.1o
100
200

300

•

~ 0

aa

0

_ _ o.aD

_

•

200

-:a .,_0_

D. 0

i~i~~-~~_D
CID_.

50

..
a

oa

0

"'-"0000000

a

~

o

==

a

"

a

300

400

Event duration (usee)

Event duration (usee)

70....------------------...,

70 r--------------------,(d) 38 um AlA
200 rpm
130 Iegf(c) 8 um Al/)~~gg ~.......
III

~60

-3

11·..... - - .
..

••,. ~~~

to 50.:til.
D
l%t
Q.

..

&

. ....
....
.. ....
.. .. .. ...... ...

~•• •- .
,.

,AMA

..

..

r

,. ..

..

.

4O~---......L----....l...------I1..-----J

o

100

200

300

4OL.-

...1....

-1..

o

100

200

400

--I

-..l

400

Event duration (usee)

Event duration (usee)Fig. 6 Cross-plot of peak amplitude vs. event duration.

>-E

-

'-'

>
E 60

(0) 200 rpm / 130 kgf

I.&.J(b) 600 rpm / 400 kgf

BO
BegiMing of.&. Injection£ndof.t,lnj lC:ticn

60

~

'-'
I.&.J

~
;..J

Beginning of~ injection

~ 40
~

~
en 20

~ 40
en
~
a::: 20

End ofInjection...

~l •. .1

c:::

.

!:i 0
0

2

~

•

6
8
4
TIME (minutes)

0

10

0

12

2

468
TIME (minutes)

10

12Fig. 7 AE nos voltage vs. time for two different rotating speed (0.1 J.1rn).
observed except for a few small spikes due to the relatively
low concentration. On the other hand, the change in AE
rms voltage level was significant when the size of particles
was increased. With the particles of 1 or 8 J.lm AE rms
voltage level increased gradually from the beginning of particle addition, while the level increased and stayed at almost
constant levels with the 38 J.lm particles. From this results. it can be said that AE method is detectable for the

4.2 Effect of Foreign Particles by Mixing in Oil BathThe effect of concentration of particles was studied bymixing particles into the oil bath and continuously circulated during experiments. Results of AE nns voltage claraobtained for the concentration of 0.01 % for each size ofparticles are shown in Fig. 8. In the case of 0.1 J.l.m particles, noticeable change in AE rms voltage level was not
660(0) 0.1 p,m (0.01%)
Beginning of
Addition

40

+

20
0

I

I

0

10

20

30

50

40

60

(b) 1 P, m (0.01 %)Beginning of". Addition40,.-...

>~20 IIw

I"~ o 0ILJL.w..-~

-

10

1• .1

-

L.J ..llil...l,'ul

20

40

30

50

:....J0> 60(c) 8 p,m (0.01%)(/)

Beginning of". Addition:::iE 40

c:::

w

« 20
0

0

10

60

Beginning of St
2 -I
Additionage40'&'1-- stgae 1 - I

20

.J

J

~.J

-

I

30

20
1 - Sta

~

ge

.

...

L£

L

L

50

40
(d) 38 p,m (0.01%)

3-1

Stage 4.L.

I-Stage 5 .......

Il.....J

o0

10

30

20

40

50

TIME (minutes)
Fig. 8 AE nns voltage vs. time with various size of particles added to oil bath (0.01%).
representative case, Fig. 9 shows the result for 38 J1m particles since there exist much more occurrence of AE events aswell as the copious change in AE nns voltage level asshown in Fig. 8(d). Rapid increase was observed at the
beginning of particle addition and more prominently inabout 10 minutes as shown in Fig. Sed) as well as in Fig.
9(a). Figures 9(b) and (c) show the distributions of eventsby peak amplitude and by energy. respectively, for the entire
experiment. The results of the analysis of distribution of
events by energy for each stage in Fig. 9(a) are shown in
Fig. 10. Increased AE nns voltage level of the early stage(Stage 1) is considered as due to the collision and erosive
action of panicles, because wear debris was not observed at
the oil outlet during the first 10 minutes. The sudden in-intervention of foreign particles having size of above I J,lm
with concentration of above 0.01 %. The entire period ofexperiment with 38 J,lm particles is divided into five stages
considering AE nns voltage pattern as in Fig. 8(d) to investigate the characteristics of AE events in various stages.
AE event vs. time and distribution of AE parameters
for each particles size were obtained. The results of distribution analysis showed the trend of unimodal distributions
by peak amplitude and of bimodal or trimodal distributions
by energy. It appeared that AE signals with larger energy as
well as the increase of AE nns voltage level was due toincreased event duration without changing peak amplitude as
was discussed with Fig. 6 in the previous section. As a7

S1age I Slage 2 Stace 3II......

Slaoe 4'"*(a) Stage 1

Stace 5)1883(, , 13 18 ZJ 2lI:D 38 43 0(8 53 58 63 foB 73 18 83 88!J3!ll1
DIST. 1 or DIDnS I I _ r rOil _ _ Z..-a or lIlnlMltS • 1811
1Il1DUAL sua • 1'::B8~:ee~I:!:::ll~~------r"----"""---;;:;~~lUDITS us t IIIE FOR SDISOlI Z
IUIllEIl OF 1"1'DlIIRLS .. 48lI-

IIl1DIWlL SIZE .. !J (S)tal•(b) Stage 2-'~3~':--::'"~13~18~Z3=--:2B~33~38~43~4~8~53~58:-:-'63::!'"""":68~73=-=78=-=83=88=-=!J3:-::::98~

DIU. 1 OF ~tS BY PEAk AllPLl1UD£ IDiU FOR SEIISOIl Z
IUlIIEI OF 1"1'DlIIRLS .. 11ll
l"tDIML S lZE .. 1<c) Stage 3(bl(d) Stage 4• '!":3=-:':-'~13::-:':18~z:a=--=2B::-=33=-=38:-43~48::-::S3::=:58~63::-:68rl73=-=78::-::83=-=.=-=!J3:-::::!l8;­
DIST. 1 OF EUDlTS BY DCEIl"I FOI SDISllJl Z
ItIlIIllEll OF IIItEIIIHlU: .. I8ll-

IIl1EIIUAL SIZE " 1<c)Fig. 9 AE events vs. time, distributions of events by peak
amplitude and by energy for the entire experiment (38 J.1rn).

D .!l,J"'6""'.-:'!I3:-I8"""'ZJ~2B="":D""""38"""'O~48"""'S3"'::;'58..-?!63~68~'7.J""18=-=lD""""'88""!J3=-=!J8:­
DIST. 1 or IUDlTS I I _Faa _ _ Z

crease of AE nns voltage (Stage 2) is an unusual phenomenon during this particular experiment and is a temporarily
unstable state caused by the local embedding or aggregationof particles whose nominal size was larger than MOFf.
The level returned to a level above that of Stage I until theend of the experiment Typical wear action may progress
actively by the particles embedded or settled to the bearing
surface during the Stages 3. 4 and S. During these stages a
lot of wear debris was observed at the oil outlet in the latterpart of the experiment They are chamcterized by features
such as the increase of rms voltage level as shown in Fig.
S(d) and the typical trimoda1 distributions of events by energy as shown in Fig. 10(c), (d) and (e). The signals withlarge energy value around 68 as shown in Fig. 10. whichwere not found in the early stage, can be classified into signals generated by typical abrasive wear. With the elapse oftime. the effect of such higb energy sources ~-_or~._~SIZl:.l(e) Stage 5

Fig. 10 Distribution of events by energy for each stage (38J.UIl).

because of the reduction of abrasive action by continuous
wear.

8

(0) 1 Jl.rn (0.01")
Beginning of
J,. Addition

40

20
0

-

0

>

15

1. .1.

20

II.1

L L..l.1

2530(b) 1 p,m (0.1")

Ole:
e:.2
c~

Co:)

~4O

~~J,.
u
a:a

:...J

~
en 20

L

r -

~

a:::

0

10

""-

0

I.LJ

<

5

IL.tL - ......

-

560

I.LJ

..

L

a

5

....

I
',",

15

10

20

80
60

25

.....

30

(c) 1 p,m (0.5")
Beginning of

J,. Addition

40

20

o0

5

10

15
TlME (minutes)

20

25

30

Fig. II AE rms voltage vs. time with panicles concentration added to oil bath (a) 0.01 %, (b) 0.1 %, (c) 0.5%.
The combination of AE rms voltage and energy distribution or waveform analysis can be used to specify the AE
sources by intervention of foreign particles in lubricant
layer. From this work it has been shown that the intervention of particles having size of above 1 J.U1l with concentration of above 0.01 % is clearly detectable. However thisvalue may vary slightly by changing the bearing dimensions (related to MOm or other experimental parameters.
In other words, the relationship between MOFT value amparticle size was very important to detect the changes of AE
signals or AE rms voltage level. Although the relationshipbetween AE rms voltage level pattern and timing on failure
was not obtained, the information for the changes or pattems of AE rms voltage level to detect initial damage ofbearing has been provided.

Figure II indicates the effect of concentration when I

J1Dl particles are introduced. The increase and the change in
nns voltage level were significant if the concentration was
higher than 0.1% as shown in Fig. I I(b) and (c). As a consequence, the larger the quantity of panicles introduced. themore AE soun:es generated. The degree of bearing damages
can be evaluated from such an increase of AE activities. It
is likely for AE nns voltage level to be maintained at a
certain level with constant concentration of impurity, but
AE rms voltage level showed a gradual increase with timein this experiment. Although wear debris was not meas\Rdquantitatively but observed visually, the amount of wear
debris incn:ased with lime. Therefore it is speculated thaI apart of particles mixed in lubricant oil appeared to be deposhed on the bearing surface and also the surface was firsl
damaged so thaI wear debris was generated by the action ofparticles, which accounted for the slow but steady increaseof the total AE activities. It was also reported that wear
rates are in direct proponion to running duration (Watanabe
et aI., 1985). In other words, the bearing daJnase is aa:umulated by repeating the wear process and is detectable bymeasuring the subtle change or increase in AE activities.

S. Conclusions
Acoustic emission technique has been applied to theearly detection of bearing damages caused by the intervention of foreign particles, which has been known as the mostprobable source of failures in the journal bearings. The
9possibility of early detection for abnormal condition is p~
vided and the distinction of the type of damage sources isverified by using AE rms voltage, waveform, AE parameters etc. It has been experimentally proved that the changeof AE activity with the size of particles can be clearly explained on the basis of theoretically calculated MOFT value.
The type of signal which resulted from the serious damageof bearing was characterized as the increase of AE energy bylonger event duration with very little change in peak amplitude. Consequently, it was confirmed that the early deIection of abnormal condition and the monitoring of damage
accumulation by the intervention of foreign particles injournal bearing systems can be realized by acoustic emission technique.

T. J. Holroyd and N. Randall (1993), "Use of Acoustic
Emission for Machine Condition Monitoring", British J.
NOT, 35(2), 75-78.
E. Kannatey-Asibu, Jr. and D. A. Dornfeld (1982), "A
Study of Tool Wear Using Statistical Analysis of MetalCutting Acoustic Emission", Wear, 76, 247-261.
P. D. McFadden and J. D. Smith (1984), "Vibration Monitoring of Rolling Element Bearings by the High Frequency
Resonance Technique - a Review", Tribology International,
17(1), 3-10.

I. Sato, T. Yoneyama. S. Sasaki, and T. Suzuki (1983),"Rotating Machinery Diagnosis with Acoustic Emission
Techniques", J. Acoustic Emission, 2(1-2), 1-10.

RefereDces
H. Adachi and H. Shoji (1981), "Rolling Contact Fatigue
and Acoustic Emission", J. Japanese Society for Lubrication Engineers, 26, 593-596.

N. Tandon and B. C. Nakra (1990), "Comparison of Vibration and Acoustic Measurement Techniques for the Condition Monitoring of Rolling Element Bearings", TriboJogy
International, 25, 205-212.

T. Akagaki and K. Kato (1992), "Ferrographic Analysis of
Failure Process in a Full-Scale Journal Bearing", Wear,
152, 241-252.

S. Watanabe, K. Saki, S. Asanabe, and M. Fukutomi(1985), "Evaluation for Wear Life of Journal Bearing Lubricated by Contaminated Oils", Proc. of the JSLE Int'/ Tribology Conference, Tokyo, Japan, pp. 85-90.

S. Bagnoli, R. Capitani, and P. Citti (1988), "Comparisonof Accelerometer and Acoustic Emission Signals as Diagnostic Tools in Assessing Bearing Damage", 2nd Int'l ConI.
on Condition Monitoring, London, England, pp. 117-125.

T. Yoshioka and T. Fujiwara (1982), "A New Acoustic
Emission Source Locating System for the Study of Rolling
Element Fatigue", Wear, 81, 183-186.

H. L. Balderston (1969), "The Detection of Incipient Failure
in Bearings", Materials Evaluation, 27(6), 121·128.
D. A. Dornfeld (1992), "Application of Acoustic Emission
Techniques in Manufacturing", NOT & E International,
52(6), 259-269.
R. C. Elwell (1985), "On-line Oil Contamination Monitor", EPRI Proceedings, EPRI CS-4024, Contract WS 81240, Proceedings: Turbine Bearings and Rotor Dynamics
Workshop, June, EPRI, Palo Alto, CA.
L. C. Ensor and C. C. Fong (1975), "A Study of the Use ofVibration and Stress Wave Sensing for the Detection of
Bearing Failure", NASA-CR-I44130, Endevco, San Juan
Capistrano, CA, Sept [NIlS: N76-15462).
D. R. Harting (1977), "Incipient Failure Detection by IJ&.
modulated Resonance Analysis", InstrUmentation Technology, Sept, 59-63.
D. R. Harting (1978), "Demodulated Resonance Analysis A Powerful Incipient Failure Detection Technique", ISA
Trans., 17,35-40.

10Clustering Methodology for the Evaluation of Acoustic
Emission from Composites
A. A. Anastassopoulos and T. P. Philippidis
Abstract

respective AE signals (Roger et aI., 1985). When classifying AE sources during damage progression in composite
materials, the training patterns are usually obtained frommodel specimens exhibiting a dominant failure mechanism(Roy et aI., 1988; Roy et al., 1990). In doing so, one ~sumes the existence of similarity between the generated AE
signals and the propagation characteristics of each failure
mechanism in the model specimen and the actual testing
specimen. For example, it is assumed that a crack formed in
the isotropic and homogeneous neat epoxy specimen will
give rise to similar AE signals with a comparable crack inthe matrix constituent of the anisotropic and heterogeneouscomposite material. However, it is known that the polymer
macromolecules due to the constraining effect of the surrounding fibers are tightly packed and ordered resulting invariations of the mabix effective stiffness and strength withrespect to those of the bulk polymer (Theocaris, 1986). On
the other hand, specimens containing delaminations are notexpected to produce signals only from delamination growthand completely isolated from other sources of AE signals,
e.g. mabix cracks. In addition, to the above cited uncertainties, there are cases where this procedure is not applicable.
For instance, in woven 3D Carbon/Carbon composites it isimpractical to perform separate tests on the matrix and reinforcement material.

Panitional clustering analysis is used for the interpretation of acoustic emission (AE) signals from glass fiberl
epoxy composite specimens in order to overcome some ofthe difficulties and uncertainties encountered either withconventional AE or with supervised pattern recognition
analysis of AE data. Two different clustering methods are
examined and procedures for numerical validation of theresults are investigated. Comparison of clustering resultswith optical microscopy is used for further validation of theresulting partitions, while the initiation and growth of thedifferent failure mechanisms is successfully characterized byplotting the cumulative events of each of the resultingclasses. The proposed method highlights the potential andeffectiveness of AE along with data clustering analysis as a
powerful stand-alone nondesttuetive testing technique for thediscrimination between various failure mechanisms.

1. Introduction.
Acoustic emission (AE) is an efficient method to monitor in real time damage growth in both sttuctural components and laboratory specimens. Prior to any conclusion on
the damage nature occmring in the malerial, the signature of
the AE signals must be identified. Conventional AE method
is often used for that purpose. The technique is based on thecorrelation of AE signal parameters with the different failure
mechanisms in the material (pollock. 1989). Such correlation is most of the times assisted by microscopic examination and/or other non-destruetive testing methods (Backucleas et aI., 1994; Eckles and Awerbuch, 1988; Salo et al..
1986).

An alternative procedure to establish the initial training
set, is either to identify and group visually the various
classes of waveforms (Kawamoto and Ono, 1989) or to use
hierarchical cluster analysis (Belchamber et al., 1985). Betteridge et al. (1983) outlined some of the problems and uncertainties encountered by using cluster analysis. For instance, the requin:d human judgment, the heuristic ~cedures involved in various stages of the analysis and theprobability that the resulting partitions will nol have any
physical significance are some of them. However, a method
to estimate the number of clusters and validate the resulting
partition was not proposed in the aforementioned work.

Pattern recognition is an alternative technique for theidentification of AE signals. The majority of the publishedarticles on the topic are dealing with supervised pattern RCognition. In cases of controlled processes. such as welding,the necessary training set for classification can be obtainedby changing the process parameters and moniloring the

The objective of the present study is to establish un·
supervised pattern recognition methodology for the identification of AE signals as an alternative or complementary
procedure to the aforementioned supervised pattern recognition techniques. The term unsupervised pattern recognition is used to describe the complete methodology con-

Received 21 December 1994. The authors are affiliated with
Applied Mechanics Section, Mechanical Engineering Department, University of Patras, P.O. Box 1401, Patras 265 00,
Greece. (philippidis@tech.mech.upatras.gr)
Joamal of Acoustic: Emissioa
Volume 13, Numbm 1/2

110730-00S0r'9SJSS.00I13011-13022

Copyrightel99S Acoustic: Emission Group

50

1600
Loading....... Cum. Chi

45
40

,:"
J:

- - - - Cum. Ch2

,:

L'

3S

1;

~ 30

(J)

1200
1000

t

~

1400

I

,:

25

~ 20

/

15

..,r

(J)

600

JlI'

400

J

10

_J

,;e-.~~"

5200---;::.--:,"

0
0

1000

[

800

l
I
I

51

0
2000

3000

4000

Tnne63ed
Fig. 1 Quasi-static loading of glass fiber/epoxy specimen.
sisting of procedures for descriptors selection, cluster analysis and cluster validity. In addition, the resulting partition
can be used as a training set for subsequent classification.
As opposed to the selection of hierarchical clustering forgrouping data in previous works (Belchamber et a1., 1985;
Betteridge et aI., 1983), partitional clustering is adopted inthis study. However, hierarchical clustering is used forgrouping the AE parameters and assist the descriptors selection.

Four types of specimens were made of Araldite GY
2501HY 2963 (100:45 by weight) Ciba Geigy epoxy system, cured 4 hIS at 60°C. The first type is a dogbone A5TM
D 638 specimen without reinforcement used both for AE
testing and to measure the mechanical properties of the epoxy resin which were found equal to: modulus of elasticity
E 2.86 GPa, Poisson ratio V 0.352, tensile strength or= 50 MPa. The remaining three types of specimens were
reinforced with Unifilo U-814 bundles of E-glass fibers
coated with polyester binder. Bundles of fibers were selected
instead of a single fiber in order to simulate the tight packing of fibers in structural glass fiber/epoxy composites. On
the other hand, the use of limited number of bundles in eachspecimen allows the measurement of the number of fiber
breaks in each bundle and enable the observation of deboRding initiation and propagation with optical microscope.
Therefore, in the second and third type of specimens one aJXI
three bundles of fibers respectively were embedded parallelto the loading axis. The fourth type contained a single bundle of fibers inclined at S° with respect to the loading axis.

=

Acoustic emission was recorded during tensile testingof glass/epoxy specimens. Two different partitional clustering methods are used to group the AE data, which contained
signals from all the different failure mechanisms in the material as well as signals arising from noise sources. Procedures for numerical validation and comparison of the resulting partitions are examined in depth. Based on the results of the validity study one of the partitions is selected
and used as training set for the subsequent classification of
AE data obtained from different specimens. Further validation of the selected partition is performed by comparing theclassification results with those obtained by microscopic
examination at distinct loading stages. The classification
results are well correlated with the observations at the microscope and the initiation and growth of each failure
mechanism is successfully described by ploning the cumulative events of each class as a function of load.

=

Optical microscopy prior to tensile testing revealed thatnone of the fibers in the bundles was broken but some voids
were formed during fabrication in the epoxy matrix. Tensile
testing was performed on a MAYES DH 1005 servohydraulie machine operating in position control. The loading for
all the reinforced specimens was kept the same with thatshown in Fig. I, corresponding to a specimen of type ll.
The AE data recmded during loading of this specimen will
be used as reference patterns for cluster analysis. The rec0rded AE data from the remaining specimens are classified according to the results of cluster analysis. Furthermore, three
specimens from each type were examined at the microscope

2. Experimental Analysis.

2.1 Specimens. Loading and Optical Microscopy.

12

Table I Average number of fiber breaks
Specimen
Type
II

IV

i·:::...~~r§liii;rts~:,~:~~" ' , : 'h":'.~'· ;1:'<~i::\~~,1:: ;.. \y~~,'.".".·:h(.'

"

" ::

115
456
175

2.2 Acoustic Emission Testing(a).

Load Stage II:25-35 MPa

20
100
79

m

·,......··('.. ··:.o.:-y:·~~~:::·~.:.:;~0.·r~t~ ,"Load Stage I:
0-25 MPa""," .t·~: {:.

., .. (j•Acoustic emission was continuously monitored during
the tensile tests by using SPARTAN AT data acquisition
system of Physical Acoustics Corp. (PAC). The AE signals
were detected by using resonant (150 kHz) transducer PAC
R15. Two transducers were attached to each specimen while
medium viscosity vacuum grease was used as coupling
agent. The nominal distance between the two sensors was
90 mm. Preamplification of 40 dB and bandpass filtering of(100-300 kHz) was performed by PAC 1220A preamplitier.
The acquisition parameters for the two active channels wereset as follows: gain 30 dB, threshold 35 dB, peak definition
time 50 I.1s, hit definition time 150 I.1s and the hit lockout
time was set to 300 I.1s.

I·::.::'J/i:0.·~:,j\7; ,'I" ;X.
(b)Seven AE signal parameters as well as the time, loadand displacemcnt wcre measured in real time by the dataacqui~ition system. Eleven new parameters were computed
in a post processing analysis. The AE descriptors examinedin this study are listed in Table 2.
Table 2 AE signal descriptors.

(c)Fig. 2 Optical microphotographs showing damage evolution in the glass fiber/epoxy material. (a) Moderate numberof fiber breaks during early loading stages. (b) Matrix crack
opening and interface debonding at the fiber ends. (c) Matrix
crack interaction and extensive fiber debonding at highloads.

#

SymbolDescription

0
I
2
3
4

TIME

Time (s)Load (MPa)
Displacement (mm)
Rise Time (1lS)CountsEnergyDuration (l.1s)
Amplitude (dB)
Average Frequency (kHz)Counts to peak
Decay Time (1lS)Counts to Decay
Rise Aver. Freq. = #9/#3
Decay Aver. Freq. =#11/#10
Rise Angle = #7/#3
Decay Angle = #7/# 10
Norm. Rise Area = #3/#6
Rise to Decay Area #3/#10
Norm. Energy #5/#7
Norm. Counts to peak #9/#4
Decay to Peak Counts # 11/#9

5

at the end of each load hold. During the first and second
loading stage, broken tibers were observed in the bundle.
The number of breaks. such as shown in Fig. 2a, wasmeasured for each type of specimen and the average of 3
specimens is given in Table I. The absence of debonding at
the tiber ends is evident from the photograph. The numberof broken fibers increases dramatically at the third loading
stage and for the specimens of type II an average of 306
breaks were measured. In addition, the new failure mechanism observed during the third loading stage was debonding,limited near to the broken tiber ends (Fig. 2b). At the lastloading stage substantial debonding propagation was observed, resulting sometimes in elongated debonding areas connecting neighboring broken tiber parts. In the worst cases
all the fibers in the bundle were debonded for certain extent
along the loading axis (Fig. 2c).

6
7
8
9
10
11
12
13
14
15
16
17
18
19
20

13

LOAD
DISP
RT
CNTS
ENE
DUR
AMP
AVF
CNP
DT
CND
RAF
DAF
RAN
DAN
RTA
RDA
NEN
CPC
CDP

=

=

=
=

Table 3 Characteristics of noise sources.
Noise TypeAMP (dB)

CNTS

Electromagnetic
Mechanical36 - 53
68 - 100

1-4
68 - 282

RT (us)1-5
79 - 230

The relatively low threshold value is used in order toenable weak noise sources to be recorded and to investigate
whether their identification is possible. Acoustic emission
signals produced by electromagnetic interference (EMI) wererecorded by using a specimen instrumented with a (00-90")
strain gauge rosette with non-isolated cables. The specimen
was fixed only at the upper crosshead grip of the testingmachine and unloaded, in order to avoid triggering from real
AE signals. The strain gauge cables were placed close to thetransducer cables and the preamplifier. Noise signals wererecorded every time the data logger digitized a measurementfrom the strain gauge. By placing the AE transducers andcables in one side of the specimen and the gauge cables on
the other side, noise has been isolated. However. as it will
be shown latter. very few EMf-like signals were recorded in
specimens without strain gauges as well. Acoustic noisefrom the gripping mechanisms of the crosshead of the testing machine was recorded during loading of some specimens. The characteristics of such mechanical noise and thepreviously described EMf signals are listed in Table 3.

RTA
0.440-0.830
0.027-0.254

DAN
0.320-0.440
0.028-0.114

clustering, to be faster in terms of central processor unit
time, requires less computer memory and above all it allows
poor initial partitions to be recovered. Three different partitional algorithms are used in this work, while Euclidean
distance serves as a measure of dissimilarity in all of them.
The maxmill distance algorithm (Tou and Gonzales.
1974), is a heuristic procedure able to identify cluster regions which are farthest apart. In our implementation thealgorithm starts with two initial cluster centers defined as
the pattern farthest to the center of the data and the pattern
farthest to the first one. A new cluster is created if the maximum of the minimum distances between each point to theexisting clusters is greater than the distance threshold. The
distance threshold for the creation of new clusters is definedas the product of a user defined parameter Tm and the average between clusters distance. If a new cluster is created itis placed at the same position with the point exhibiting the
maximum distance. Values of Tm range in the interval (O,I)
and the smaller the value of Tm the larger the resulting
number of clusters. This is the only user defined parameterrequired by the algorithm which can also be used as an estimate of the number of clusters in the data set as it will beshown later.

3. Unsupervised Pattern Recognition.

3. J Cluster Analysis and Validity Indices

On the other hand, the K-Means and the adopted versionof Forgy's algorithm are iterative procedures which aim tominimize the sum of squared error for a given number ofclusters. K-Mealls algorithm (Tou and Gonzales, 1974),
starts with a number of C initial clusters, set by the user. In
our implementation of the algorithm, the C initial cluster
centers are selected at random from the entire data set. Thenassignment of the remaining points to one of the C classes
is performed by nearest neighbor classification. The cluster
centers are updated as the mean vector of the resultingclasses. The process continuous until none of the patternschange class membership. The modified Forgy algorithm(Dubes and Jain. 1976) is an extended version of K-Means
supplemented with heuristic procedures for the creation of
new clusters and the omission of existing small clusters
with fewer than the minimum desired patterns in each class
Nmin' A new cluster is created if a pattern is sufficiently
separated from the existing clusters. A user supplied parameter Tr taking values in the interval [0, I) is used to control the creation of new clusters. A new cluster is created at
the position of pattern i if:
ID~v - D~I < Tr D~(I)
where D~v denotes the average distance between point i andall the existing clusters and D~ denotes the distance between point i and its nearest cluster. Therefore the numberof clusters increases by increasing the value ofTr.

The pattern vector, i.e. the description of each signal,must be composed from features able to discriminate between the different sources of AE signals. In the absence of
any a priori knowledge about the classes, features selection
cannot be based on discriminant analysis and criteria such as
Wilk's A applicable for the case of supervised pattern recognition (Roy et al. 1988). However, in pattern recognition
analysis it is often suggested to use the smaller possible
number of uncorrelated descriptors. Therefore, the correlation matrix of AE parameters is subjected to hierarchicalclustering in order to define groups of uncorrclated descriptors. Each AE parameter is initially considered as an independent variable. Then the two most correlated descriptors
are merged in one and a new cluster is formed followed by
an update of the correlation matrix. The merging processcontinues until all descriptors are placed in the same group.
Different techniques are defined by varying the update procedure of the correlation matrix. Two selected techniques
known as Single Link and Complete Link are implemented
in software according to the description given by Anderberg(1973). The results are presented in dendrograms, showing
the merging sequence at each correlation level.
Partitional clustering is used to group the AE signals
in a small number of classes compared to the total numberof patterns. It offers the advantage, compared to hierarchical

14

The Rand statistic is based on the pairwise classification table (Table 4). computed from the class labels of theindividual patterns in each partition. The cell a in Table 4.
indicates the number of pairs of patterns classified in thesame class in each partition. while d represents the numberof pairs classified in different classes. On the other hand. b
indicates the number of pairs of patterns placed in the samecluster in partition 1 and in different cluster in partition 2.
while c stands for the opposite. The Rand statistic is definedas: (a+b)/(a+b+c+d) and can be used to compare partitions
with different number of clusters as well. Formulas forcomputation of elements a to d of Table 4 are given by Milligan (Milligan et a1.. 1983). When the two partitions are
identical the Rand value is one. while the theoretical lower
limit for completely different partitions is zero.

The evaluation of clustering results is based on the R
criterion. defined by Davies and Bouldin (1979). The criterion relies on the calculation of:
Dj+D jR jj = D.. • i.j =1....C(2)
IJ

where. Dj and Dj denote the average within-class distance ofclusters i and j. respectively. Djj denotes the distance between the two clusters i and j and C is the number of clusters. Denoting by ri :rj = max{R;j}''Vi ~ j. i. j = I.....C
the criterion is defined as:
I C
R=C j=1

L/j.

(3)

(4)

The lower the value of R the better the clustering.

Table 4 Pairwise classification table

Another criterion based on the computation of Dj ml
Djj had been proposed by Tou and defined (Bow. 1984) as
follows:
A.=min{Dij}/max{Dt}.

i. j. k = 1•.u.C

Partition 1

Partition 2# of pairs not in thesame cluster
same clusterab# of pairs in the(5)# of pairs in thesame c1usler# of pairs not in
the same cluster

According to the above definition, the criterion combines
only the extreme values of Dij and OJ. Thus•. it has been
adopted as complementary to the R criterion which is anaverage measure of compactness and separability with respeet to the existing clusters. The higher the A. value, thebetter the clustering.

cd

3.2 Identification of Mechanical Noise and Descriptors Selection.

Comparing the above criteria with those based onwithin-class scatter matrix. they have the advantage to be
independent of the number of classes. 11lerefore, it has been
proposed to estimate the number of classes by plotting thecriterion value versus the number of clusters and searchingfor that number. which minimizes (maximizes) the criterion
value. In this procedure. the criterion value is computed byusing the same descriptors with those used for the clusteringreferred in what follows to as relative index value. If one
wish to compare partitions produced by different descriptor
sets the criterion value should be computed by using a new
descriptor set common (or all partitions. In that way one
finds the best partition among those considered with respect
to the specific criterion and the specific descriptor set used
for the calculation of the criterion value.

Mechanical noise was successfully identified and separated from the AE data by using the maxmin distance algorithm. Amplitude. counts and duration were used as repre-

sentative AE parameters for that purpose. A value of Tm =0.4 was set as input parameter in maxmin distance algorithm and the resulting partition is given in the scatter plotof Fig. 3 displaying counts vs. amplitude. Although theresults were obtained by using all of the 2960 recorded AE
events, only a representative part of those points is plotted.
From the two different noise sources indicated in Fig. 3. thefirst one was verified in real time. The second one contains
data very close to the real AE data and it was not easy toverify in real time which event represent a noise source ml
which a real AE signal. However. there exist consecutive
AE events recorded from each channel and recognized one as
a 1st noise type and 'the other as a 2nd noise type. indicatingthat some of the lower intensity events of the 2nd noise
type represent attenuated signals of the lst noise type.
Similar results were obtained for a value of T m = 0.5. Inthat case some data points with less than 90 counts had
been assigned to the remaining AE data and not to the noiseclass. AE data arising from mechanical noise were considered as outliers and removed from the data set for the subsequent cluster analysis and cluster validity.

Comparison between two different partitions independent of the descriptor set is performed by computing theRand statistic (Rand. 1971). The criterion does not yield any
infonnation on the compactness and separation between the
resulting clusters and is used to examine the similarity between two different partitions. Comparison of different partitions is essential in order to assess the effect of the clustering parameters on the results. Furthennore. it is imponant
to know if similar partitions are obtained by using different
clustering methods and/or different descriptor sets. If so. it
can be considered as a validity indication of the resulting
partition.

Grouping of AE parameters. according to their correlation coefficients is perfonned by using the Complete Link
15

300
[J

250

en

.+.

IJ Acoustic noise I• Acoustic noise II
OAEdata

g

200

CI

C

a

CI

ISO

A

CI

U

[J

100
A.+. Ai

A

A

SO

~

6ffio

0
30

40

SO

A

~OcP~

60

70

0

80

A

AA
AtJ.

0

90

100

AmpIitude~

Fig. 3 Mechanical noise identification using the maxmin distance clustering algorithm.

1.00
0.97

y'T'".. ,,,, ...,, . .

Descriptor Number
S II • 1\ 6 10 7 10 16 19 IS 17) 9

IS 17

1:~ I

1.00
G.97

a IJ 11 14

1

..
0.70

0.70

]
.§

1

OJ,

u

0.16

o.t6

.... ..-00

T

M

Fig. 4 Correlation of AE descriptors (a) with and (b) without noise events in the data set.
16~

algorithm applied on the reference AE data obtained from a
specimen of the second type where a single bundle of fibers
is embedded parallel to the loading axis. The same groups ofuncorrelated descriptors were found by using Single Link
algorithm, although the absolute value of correlation at eachclustering stage was different compared to that resulted byComplete Link. The two dendrograms of Fig. 4 summarize
the correlation of AE parameters in the presence of mechanical noise (Fig. 4a) and by removing it in the way previously described (Fig. 4b). Comparison between the two
dendrograms indicate that AMP(##7) has changed position
after removing extraneous noise and moved to the samegroup with counts, energy and duration. Minor changes canbe observed for the remaining descriptors as well. The results, are in accordance with the suggestion for noise identification from the scaner plot of counts versus amplitude(Pollock, 1989).

ds4 = {RT. AMP. DAN. RTA. COP}.
As it can be seen from the above definition the third descriptor set contains both AMP and CNTS. while the fourth one
is defined by removing CNTS in order to investigate theeffect of using two highly COIrelated descriptors in the ~scriptor set.

3.3 Clustering Methods
A clustering method is established in the present study
based on the combination of maxmin distance and modified
Forgy algorithms. The maxmin distance algorithm is used
to create an initial partition which is further optimized byusing modified Forgy.
The entire methodology was tested with artificial da1a
sets, composed of clusters of previously known classification. Each pair of clusters was completely separable at leastin one of the 20 plots of the different variables used. The
tests were performed for different number of descriptors.
different number of clusters and different portion of points
in each cluster. Descriptors of each cluster were generaledeither from Gaussian or from uniform distribution. The
maxmin distance algorithm with Tm = 0.5 predicted thecorrect number of clusters although the correct partition of
the data was not always recovered. Partition refinement byrunning the modified Forgy algorithm starting from thepreviously found cluster centers by using maxmin di.sttmce
algorithm, resulted in the correct, a priori known. clustering.

Descriptors for grouping the remaining AE data wereselected by cuning the dendrogram of Fig. 4b at correlationlevel equal to 0.7 resulting in nine groups of uncorrelated
descriptors. Some of these groups were discarded as useless,since the histogram of the corresponding descriptors did notexhibit sufficient variability with respect to expected valleys
and peaks. Furthermore. selection of descriptors within edl
group is assisted by using histogram plots as well as byexamining the variation of each descriptor as a function of
the applied load. Based on the above procedure. the AE ~scriptors selected for the discrimination of different failure
mechanisms and the remaining noise sources are: RT.
CNTS or AMP or DUR, DAN. RTA and COP.

The same methodology was applied on real AE data. In
that case, some experimentation was necessary in order toselect the input parameters for the two algorithms. Two
different combinations of Tm and Tr were found appropriate
for the needs of AE data. By using Tm = 0.5 the number ofclusters may be underestimated by maxmin distance and an

Four different combinations of the above descriptors areused for the partition of AE data as follows:
dsl = {RT. CNTS. DAN, RTA},
ds2 = {RT. AMP. DAN, RTA}.
ds3 = {RT. AMP, CNTS. DAN. RTA, COP}.

Table 5 Perfonnance criteria values.
Oustering Parameters
Descriptors AlgoritJun parameters
Set I
Set I
Set I
Set 2
Set 2
Set 2
Set 3
Set 3
Set 3
Set 4
Set 4
Set 4

Tm = 0.5.Tr = 0.3
Tm OA,Tr= 0.2
K-MeansT m = 0.5,Tr = 0.3
T m = O.4,Tr=O.2
K-MeansT m = 0.5,Tr= 0.3
T m = 0.4,Tr= 0.2
K-MeansT m = 0.5.Tr= 0.3
T m 0.4.Tr= 0.2
K-Means==

Number of
Clusters

R
Relativel
RelativeR
GloballGlobal

7
7
5
7
6
6
7
6
7
7
8
5

0.94880.75890.79470.77210.72940.7286
0.98630.86990.79080.92970.80070.74251.29081.31051.45381.2872
1.32451.33190.9877
1.14651.16181.27511.35561.56971.77781.47791.3062
1.51661.41671.41101.62161.47371.4124
1.6745
1.63611.25130.23020.23220.28110.24530.25720.25780.19900.21980.22990.23940.23190.3040

17

100
+~

•

++...
..+• • :

90
80

.

70

+

(a)

50

.

40

~

+.

°

Class 3

+ Class 4_=_--'-Class5

X X_

Class 2":1:
cg\ lx 1...X+t~~ .;' +."t.t~

1X X

to ~oN" " '!II~~0

60• Class I~ClassO

+

--

-t:

I

#

•

• ~,I

0

"'t

,~

30

o

10

20

,

0.9

SO

40

60

~Class 0.-., -

0.7
0.6

~ O.S

70

80

90

o Class 2+ Class 4- Class S

•

OeP

0.3

110

• Class 1

I

0.4

100

Rise Time (JlS)

• •••

0.8
(b)

30

••• • •

•

0.2

••
,
.-

0.1

o

o

10

20

30

40

SO

60

70

80

90

100

110

Rise Time (J.1S)
Fig. S Clustering results from proposed method. Descriptor set: {RT, AMP, DAN, RTA}.

=

input value of T r 0.3 at modified Forgy was used as amean to increase the number of clusters jf necessary. On theother hand if T m 0.4, the number of clusters is overestimated by maxmin distance. Subsequent clustering withmodified Forgy will delete small clusters. A value of T f =0.2 is necessary to recover some of the previously deleted
clusters. The scatter plots of Fig. 5 present the clusteringresults on AE data from the reference specimen of type n.
For this case the 2nd descriptor set i.e. {RT AMP, DAN,
RTA} was used, while the clustering parameters were T m
0.4, T f = 0.2 and Nmin = 16. Figure Sa displays the scatterplot of AMP vs. RT. while Fig. Sb the scatter plot of RTA
vs. RT.

on. Table 5, summarizes the calculated R and A. values forthe panitions obtained by using the two different combinations of Ts as well as for the resulting partitions from thesecond clustering method, description of which is given inparagraphs bellow.

=

1be term relative is used to denote that the R and A
values are calculated by using the same descriptor set as forclustering, while the tenn global denotes that the R and A
values were calculated by using a common to all partitions
descriptor set composed by the following descriptors: #{ 3,4. S. 7. 8.9. 12. 13, 14. IS, 16. 17. 20}. As it can be concluded from Table S. the results obtained by using Tm = 0.4
and Tr =0.2 are more relevant for the partitions of the AE
data since a better clustering is achieved compared to thealternative combination of T m 0.5 and Tr
0.3. 1be=

The selection of the proper combination of T m. T f arxI
Nmin. can be assisted by using either the R or the A criteri-

=

18

=

above results indicate that it is preferable initially to overes·
timate the number of clusters than to underestimate it.
However. the differences are small and sometimes they cannot be visually detected by observing the corresponding
scatter plots of each panition.

established method with an alternative one based on KMeans algorithm. Partitions were produced starting from 2
clusters to 20 clusters. Thiny runs of the algorithm were
perfonned for each number of clusters. starting from different initial cluster centers selected at random. The R criterion was computed for the 570 different partitions amplotted versus the number of clusters. Figure 6 shows theminimum R value and the average R value estimated after
the thiny runs for each number of clusters for the 2nd descriptor set. The global minimum is achieved for 6 clusters
which is the same with the resulting cluster number fromthe first clustering method. The same procedure was followed for the other descriptor sets. However, the estimatednumber of clusters from the two methods was different for
the remaining descriptor sets. The resulted number of clusters and the corresponding optimum R and A. values are
given in Table 5. When referring to the relative indices.
similar results were obtained from both methods while aslightly better clustering is achieved from the proposed
method for the first descriptor set. On the other hand, if one
compares the global R and A values, the multiple ruils of
K-Means resulled in a better criterion value in all cases.
However, such a conclusion is valid only for the specificdescriptor set and can change for a different one. Nevertheless, comparable R and A. values were achieved in bothcases. Further comparison of the two methods for each descriptor set is performed by means of Rand statistic and ispresented in Table 7.

Further comparison of the resulting panitions for thetwo different combinations of 1"s is perfonned by means ofRand statistic and the results are given in Table 6. Each of
the main cells of Table 6 contains the calculated Rand value
for the pair of partitions indicated in the first row and column. For example, a Rand value of 0.906 was found bycomparing the panition produced by using Tm 0.4. T f
0.2 and the 1st descriptor set with that obtained by using
Tm =0.5, Tf =0.3 and the 2nd descriptor set. Similar results were obtained for the two different combinations of
1"s, since for 3000 patterns, 4-6 descriptors and 5-7 clusters,
Rand values greater than 0.75 indicate similar panitions.

==

The suitability of the above mentioned values of Tm =0.4 and Tf 0.2 is verified by comparing the results of the=Table 6 Rand statistic for the two different combinations ofTmand Tf·
Tm=O.4 TrO.2
NmiD=16

Tm=O.5. T,=O.3. NmiD=16

descriptor set(l11ID1ber ofclusters)

1
(7)

2
(7)

3
(7)

4
(7)

1(7)

0.943

0.906

0.865

0.857
US8
0.791
0.899

2(6)

0.833

0.949

0.809

3(6)

0.723

0.744

o.m

4 (8)

0.813

US8

0.846

Similar results were obtained in general as it can beseen from Table 7. while the highest similarity was achieved by using the 2nd descriptor set where a RmuJ value of
0.994 is calculated. The lowest Rand value encountered wasequal to 0.736 corresponding to the panitions produced byusing the 4th descriptor set and is probably due to the difference in the number of clusters.

1.4

1.3

des. set 2

1.2~Minimum-D-Average

1.1

R

1.0
0.9
0.8
0.7

0.6
2

4

6

8

10

12

14

16

Number of Clusters
Fig. 6 Determination of number of clusters.
19

18

20

III3X

1220.
.

....... Clurl---_.. Clur2
ClasJ

800

I

_.

700

I

I

--

Clur4

-

ClasS

LoadiDs

StqcIv

LoadiD8_ 1-~8._ J
Stage
SCasenlII'

LoadingnSmge Ir'-,..- ".....-.-.
*'-!.
.
.... - .. ,...,' - _
J
-

200

J

- -"..

l

~_.

100

~.

o

o

20

10

",

,

.'

30

40

so

Stress (MPa)Fig. 7 Cumulative events of each class vs. load.
Table 7 Rand statistic for the two methods.
Combined Use of
maxmm -Forgy

K-MeBDS
I
(5)

2

3

4

(6)

(7)

(5)

1(7)

0.774

0.873

0.808

0.677

descriptor set(number ofclusters)

2(6)

0.839

0.994

0.861

0.768

3(6)

0.837

0.773

0.896

0.770

4 (8)

0.823

0.895

0.900

0.736

Uncertainties for the validity of the estimated numberof clusters and the resulting partition arise in both methods
and none of the results should be considered as the uniquesolution to the partition problem since it is not possible toverify every somce of AE in real time.

4. Classification Results and Comparison with
Optical Microscopy.
A training set for further classification is defined by using the results obtained from the established method appliedon the 2nd descriptor set The training set was supplemented
with the data of the two types of acoustic noise, identified
during the preprocessing stage and will be refem:d to asclass #6. The characteristics of the 6 different classes of AE
signals resulted from the proposed clustering method areshown in the scatter plots of Fig. 5. One of these classes
namely #0, has similar characteristics with the EMI signals
i.e" low rise time and very few counts. The remaining fiveclasses are characterized as follows. Class ##1 is composed of
AE events with low amplitude and counts and it is the closest to the EMI-like patterns. Class ##2 consists of medium
intensity AE events, i.e. 45-65 dB amplitude. Class ##3 ismainly composed of medium to high (up to 80 dB) ampli-

tude events and increased rise time. Such events were identified as fiber/matrix debonding. Multiple fiber breaks resulting in very high amplitude events are represented by patterns of class #4. Finally, class ##5 is characterized by AE
events of rise time greater than 70 I.1S and observed just before specimen final failure. The generating mechanism ofsuch events may represent either severe debonding areas ofthe entire fiber bundle and the matrix (Fig. 2c) or superimposed AE events similar to those of class ##4.
The k-nearest neighbor classification rule (Too ani
Gonzales, 1974) is used to classify the AE events n:c:orded
during the different loading stages of those specimens examined with the microscope and the results are given in Table

8.
As it can be concluded from Table 8. the EMI signals
are closely related to the low intensity AE events resulting
in confusion between the two classes. However 62% of thereal EMI signals were correctly identified by the classifier.
Furthermore the low intensity AE signal recorded duringloading of the specimens exhibit a stable increase with load.
On the other hand. the EMI sources recorded during loadingof the same specimens did not show such an increase. Only
low and medium intensity AE signals of classes ##1 and ##2
are encountered in the neat epoxy and during the first two
loading stages of the reinfon:ed specimens. 1berefore thosesignals should be attributed either to matrix failure or 10
fiber fracture, AE signals of class ##3 and ##4 start to appear
at the 3rd loading stage and increase rapidly during the lastloading stage indicating that the classification results arewell correlated with the observations at the microscope,according to which debonding started at the third loading
stage and at stress levels greater than 3S MPa

The classification results, presented in Table 8, are further compared with the average number of fiber breaks forS. Conclusions

the three types of specimens as shown in Table I. For the
specimens of type ill, an average of 100 fiber breaks wasfound for the first loading stage. For a specimen of the same
type (Table 8), 209 AE hits in total were recorded in bothchannels. i.e., approximately 105 AE events. As the 92%of the 209 AE hits were classified in classes #1 and #2,
while only 7% in EMl-like class #0, the classification results agreed well with those revealed by the microscopic
examination. The same conclusion holds true for all thereinforced types of specimens for the ]st and 2nd loading
stages. For the third loading stage of the specimens of typen an average of 191 new fiber breaks were found. At thesame loading stage for a specimen of the same type (Table8),80 events (159 hits - 39%) were classified in classes #0
and # I and 46 events (93 hits - 23%) were classified in class#4 denoting multiple fiber breaks. Thus, it is possible thata relatively small number of fiber breaks were recognized as
debonding.

An unsupervised pattern recognition method suitable
for the discrimination of AE signals is established. The
method consists of a combined use of maxmin distance aId
modified Forgy clustering algorithms. Hierarchical groupingof descriptors provides useful information for features selection, while heuristic judgment and experimentation further
assist the definition of the most relevant descriptor sets. The
limitations of hierarchical clustering in analyzing small da1a
sets were overcome by using partitional algorithms and all
the clustering results were obtained by analyzing almost
3000 patterns. In fact, the personal computer implementation of the method does not pose any constraint at all on
the data set size.
Numerical validation is a tool to overcome some of theuncertainties encountered during cluster analysis since withthe currently available techniques it is impossible to define
a unique partition. Experimentation for different combinations of algorithm parameters. TID and T r• and by using
various descriptor sets along with parallel examination of
the resulting partition seatter plots increases our understanding on AE results and enables one to make assumptions on
the possible association between AE parameters and thesource of AE signals.

Interpretation of clustering results on a macroscopic
level is performed by plotting the cumulative events of eachclass vs. load as it is shown in Fig. 7. Referring to the cumulative plot of each class in Fig. 7, the classes #1 and #2.
exhibit higher slope during the first loading stages, whileclasses #3 and #4 become critical after the third loading
stage. Finally. the class #5, start immediately before thefinal failure. Therefore. the different damage stages in thematerial are successfully characterized by this plot.

Table 8 Classification results.
Spec.
Type

Load
Stage
MPa

Classification of AE Sources
Total Number of Bits Recorded in both Chanels

Class IClass 2 Class 3 Class 4Class 5 Class 0 Class 6

-

14

010

4

6

0

0

1

0

9

25
48
52
125

21
164
107
69

I

15
146
1083

1
18
93
1051

0
1
0
14

I

n

0-25
25-35
35-45
45-faiL

I

2
1
4
9

m
m
m
m

0-25
25-35
35-45
45-faiL

62
206
278
449

132
426
1416
2507

0
10
244
1135

0
7
409

0
0
0

2708

22

15
19
38
27

2
0
2
17

IV

0-25
25-35
35-45
45-faiL

65
29
125
161

54

1
2
497
848

0
3
258
467

0
0
0
1

5

2
0
2
5

EM!
Epoxy

26

failure

U
U
U

IV
IV
IV

108
348
234

21

1
4

0

14
1

Validity studies should be considered as procedures forselecting some of the resulting partitions for further study.
In doing so, the procedme inttoduced herein sua:eeded to
distinguish the different noise sources and to classify thereal AE signals to meaningful classes closely related withthose revealed by optical microscopy.
On a macroscopic level, the cumulative plot of theevents ofeach class vs. load clearly indicates damage initiation and progression of each failure mechanism and thus,
the severity of each class can be identified whether or not
successful characterization of the corresponding AE sourceis achieved. Therefore, the progressive damage states of thematerial are characterized by the activation of the different
signal classes and one is not interested in the slope of the
cumulative events curve but in the existence of signals fromeach class. Further quantification of the damage state can beobtained by examining the relative proportions of each classduring a certain loading interval or proof loading.
The proposed method highlights the potential and effectiveness of AE along with data clustering analysis as a
powerful stand-alone nondestructive testing technique applicable directly on the specimen under examination, instead ofusing model specimens to generate AE from idealized failuremodes, used subsequently for data classification emitted
from aetuaI structural components. The results presented in
the above indicate that it could be worthy to investigate theuse of the procedures introduced herein for analyzing AE
data from field testing on large structural components.

References
M. R. Anderberg (1973), Cluster Analysis/or Applications,
Academic Press, New Yark.
J.G. Bakuckas, W.H. Prosser and W.H. Johnson (1994),"Monitoring Damage Growth in Titanium Mattix Composites Using Acoustic Emission", J. Compo Mat, 28(4),305-328.
RM. Belchamber, D. Betteridge, Y.T. Chow, T. Lilley,
M.E.A. Cudby and D.C.M. Wood (1985), "Evaluation ofPattern Recognition Analysis of Acoustic Emission fromStressed Polymers and Composites", J. Acoustic Emission,
4(4), 71-83.
D. Betteridge. P.A. Connors, T. Lilley, N.R Shoke and M.
E.A. Cudby and D. C. M. Wood (1983). "Analysis of
Acoustic Emissions from Polymers", Polymer, 24, 12061212.
S. Bow (1984), Pattern Recognition-Application to Large
Data-Set Problems, Marcel Dekker. Inc.• New York aid
Basel.
R.W.Y. Chan, D.R. Hay, V. Caron, M. Hone and D.R.

Sharp (1985), "Classification of Acoustic Emission Signals
Generated During Welding", J. Acoustic Emission. 4(4),115-123.
D.L. Davies and D.W. Bouldin (1979), "A cluster separation measure", IEEE Transactions on Pattern Analysis andMachine Intelligence, PAMI I, 224-227.
R. Dubes and A.K. Jain (1976). "Clustering techniques: theuser's dilemma", Pattem Recognition, 8. 247-260.
W. Eckles and J. Awerbuch (1988). "Monitoring Acoustic
Emission in Cross-Ply GraphitelEpoxy Laminates During
Fatigue Loading, J. Reinf. Plastics Comp., 7, 265-283.

K. Kawamoto and K. Ono (1989). "Pattern Recognition
Analysis of Acoustic Emission Signals from Carbon FiberlEpoxy Composites", Proc. Third International Symp.
on Acoustic Emission from Composite MareriJJls (AECM3), Paris, France, ASNT, Columbus, OH, pp. 230-239.
G.W. Milligan, S.C. Soon and L.M. Sokol (1983), "Theeffect of cluster size dimensionality, and the number of clusters on recovery of true clusters structure". IEEE Transactions on Pattern Analysis and Machine Intelligence,
PAMI 5, 4D-47.
A.A. Pollock (1989), "Acoustic Emission Inspection",
Metals Handbook, Vol. 17. 9th edition, ASM International.
Metals Park. OH, pp. 278-294.
W.M. Rand (1971), "Objective criteria for the evaluation ofclustering methods", J. Am. Stat. Association, 66, 846850.
C. Roy, A. Maslouhi, D. Gaucher and Z. Piasta (1988),"Classification of Acoustic Emission sources in CFRP
assisted by Pattern Recognition Analysis". Canadian Aer0nautics and Space J.• 34(4),224-232.
C. Roy. A. Maslouhi and M. Ghorba (1990), "Study ofFailure Processes in Fiber Reinforced Composites using
Acoustic Emission Techniques", Impact 0/ Emerging NDENDI Methods on Aircraft Design, Manufacture and Maintenance, AGARD CP462. pp.24.1-24.l4.
N. Sato, T. Kurauchi and O. Kamigaito (1986). "Fracture
mechanism of unidirectional carbon-fiber reinforced epoxy
resin composite", J. Mat SeL, 21, 1005-1010.
P.S. Theocaris (1986), ''The concept of Mesophase Mechanisms of Crack Propagation", Metal-Filled Polymers. Properties and Applications. ed. S.W. Bhattacharya. Marcel
Dekker Inc.• New York and Basel. pp. 259-333.
J.T. Tou and RC. Gonzales (1974), Pattern Recognition
Principles, Addison-Wesley, Reading. MA.

Investigation of AE Signals Emitted from an SiOx Layer
Deposited on a PET Film
Masa-aki Yanaka, Noritaka Nakaso, Yusuke Tsukahara and Nelson N. Hsu
Abstract

method of mechanical strength of the glass coating on plastic film must be established. Wojciechowski and Mendolia(1992) have explored this new field. As shown in a later
section. the observation of cracks by optical microscopy isa straightforward method, but it becomes difficult when therefractive indices of the glass coating and plastic film areclose or the coating is sandwiched by the plastic films.

Fracture process of SiOx glass coatings deposiled on
PET films was investigated by experimental and theoreticalanalyses of acoustic emission (AE) signals recorded in tensile tests. Thicknesses of the coating and PET film were
SOO nm and 12 J,lm, respectively. AE signals in the fr&.
quency range from 20 to 120 MHz were detected by a ZnO
piezoelecttic transducer sputtered on a flat end of a fusedquartz buffer rod. The transducer was coupled to the specimen through a water droplet. Two distinctively different
types of AE signals were observed and identified to cracks
and delaminations, respectively.

Acoustic emission (AE) at very high frequencies pr0-

posed by Chubachi and his collaborators (Kanai et al..
1992) is an alternative way to characterize the &acture ofthin films. Nakaso and Yasujima (1993) showed that AE
signals generated by the fracture of an SiOx coating on a
PET film could be detected. In this paper. detail examination of the 100 MHz band AE signals is given and compared with theoretical analysis.

1. Introduction
Thin glass coatings on plastic films are attracting anen-tion in the packaging and printing industry because they are

2. Specimens and Experimental Method

a promising candidate for transparent gas barrier films(Anon.• 1992). Conventionally, aluminum coatings areformed on plastic films by the vacuum evaporation to ~vent oxygen molecules and water vapor from penetrating
through the films. The vacuum evaporated aluminum is an
excellent material except for being opaque. One cannot see
what is inside the package. Therefore, a glass coating islooked for as a material for the transparent gas barrier film.
An SiOx coating on a polyethylene terephthalate (PET)film is an example being successfully developed. Coating
thickness ranges from tens to hundreds nanometers.

An SiOx coating was deposited on a PET film by vacuum evaporation. Oxygen content, x. was about 1.7 measured by X-ray photoelectron spectroscopy. Thicknesses of
the coating and PET film were SOO nm and 12 J,lm, respectively. Specimens with a rectangular shape. 10 mm x 20mm. were cut from a sheet of the film and used in tensile
tests.

Figure 1 shows a block diagram of the experiment.
During the tensile tests. a piezoelectric transducer was coupled to the specimen with water, and AE signals which weregenerated by the fracture of a coating and radiated into water
were detected. In order to obtain the directivity pattern of the
AE radiation into water, a planar transducer was employed
instead of a point focus transducer used in the previous
study (Nakaso and Yasujima. 1993). A ZnO piezoelectric
film of 4 mm x 4 mm was deposited on a flat end of a fusedquartz buffer rod for the transducer. and the other end of therod was in contact with water. The effective frequency range
was from 20 to 120 MHz. With this transducer it was impossible to identify the fracture location. but the radiation
pattern could be obtained with 1° angular resolution. A preamplifier of 33 dB from de to 250 MHz and a low pass filter
with a cutoff frequency of 120 MHz were used.

A difficulty is that the coated glass is brittle while thefilm must be flexible. When the film is bent or stretched.
cracks might be induced in the glass coating and the gas
barrier capacity might degrade. Hence, the characterization

Received 8 March 1995. M. Yanaka, N. Nalcaso and Y. Tsukahara are affiliated wirh Toppan Printing Co., Ltd., TechnicalResearch Institute Sugito-machi, Kitakatsushika-gun, Saitama
345, Japan (yanaka@tri.toppan.co.jp) and Nelson N. Hsu iswith National Institute of Scandards and Technology. Gaithersburg. MD 20899 USA. Based on a paper that was given at the12th International Acoustic Emission Symposium. Sapporo,
Japan and was included in the proceedings, Progress in Acoustic
Emission VII. JSNDI. Tokyo. Japan.

Journal or Acoustic Emission
Volume 13, Number 1/2

Z3

0730-00SOI9SI$S.00/13023-029

Copyright~I99S Acoustic Emission Group

Digital
volt
meter

Digital
LPF 1----1 oscillo.

Computer(a)

Planartransducer

Stagecontroller

et=====:=!J

t----------I~f---_T-.L-----SiZ,.,;,...,joupler(water droplet)
Tilting angle e

.

ZoO
~
piezoelectric film .....

I(b)

Buffer rod(fused quartz) ~;/,PET 12J.Lm--...-----~

Rotation center

SiOx500om

Fig. 1 a) A block diagram of the experimental setup. b) A close-up view of the sensor and specimen. The rotation center was
kept I mm above the specimen's surface in measurement

In the experimental procedure, both edges of a specimen
were held between 0.5 mm-thick silicone rubbers to apply
the tensile force uniformly, and the specimen was set in atensile stage. Water was coupled to the PET film, not to the
SiOx coating, because it was suspected that the coating
strength would degrade if it had been touched by water. In
order to align the piezoelecbic transducer nonnal to thespecimen, an elecbical impulse was applied to the transducer and a reflection signal was maximized by the adjustment of stages. Then, the transducer was tilted to a determined angle by the 9-stage at which the measurement was
made. The specimen was sttetehed in the tensile tests at astrain rate of 2.5 x 104 /s, or 5 pmIs. and the number of AE
signals was counted and recorded at each 20 Jlm increment
A waveform of the last AE signal at each increment wasalso recorded and analyzed by fast Fourier transform. Anedge type trigger was used in the Tektronix 644 oscilloscope with 1.40 mV of a trigger level, which was larger
than the noise level. The strength of the tensile force wasmonitored by a load cell attached to the tensile stage.

3. Experimental Results

3.1 Observation by Optical Microscopy
Before conducting the AE experiment, a tensile test was
conducted with the same condition under the optical microscope to observe the fracture process of the SiOx coating.
Photograph I shows two distinctively different types offracture: cracks and delaminations. Cracks were first observed at 0.5% strain, and delaminations began at about 8%.
The cracks were extended in the direction pelpCndicular to150,..--------------,ooE-E....., 100

o

~

o

.~

o

0

0

0

ell

'l:J

~

E

u

SO
o

o
o

o
o
o

.......- .........~--_r_-..-I

OOO------~

o

5

10

15

Strain (%)
Fig. 2 Number of cracks in the tensile tesL

40
20
Photograph 1 Observation by optical microscopy. The direction of applied tensile force is also shown by white arrows. a) S% strain. Many cracks were seen in the normal
direction to the tensile force. b) 21% strain. The coating
was broken into segments and some were detached from thesubstrate (delaminations).

.!!4
cu

3.2 AE Signals

First, a PET film without SiOx coating underwent thetensile test and no AE signals were recorded. Next. a seriesof tensile tests of coated specimens were made with different
tilt angles of the transducer, and AE signals were recorded.
Figure 3 shows the number of AE signals as a function of
the strain.

15 deg.

.- 20
C
DO

-l I)

"C

cu

the tensile force direction, and more or less uniformly disbibuted. Number of cracks in a unit length was counted in
the tensile test (see Fig. 2). The relationship between thenumber of cracks and the fracture strength of coatings werediscussed in detail in Wojciechowski and Mendolia (1992).

0
40

u

cu
cu

"C
eo..

0
40

Q

""
e
cu

20

.t:I

= 400

Z

20
0
40

With the tilt angle of 00, no AE signals were detectedin the strain range from 0.5% to 8% where cracks had been

20

observed with the optical microscope. On the other hand.
many AE signals were detected in the strain range from 15%
to 30% where delaminations had been observed. With thetilt angle other than 0°, AE signals were detected in thestrain range of cracking, and the number of the AE signals
increased with the tilt angle up to 35° and then decreased. It

0
0

5

10

15
20
Strain (%)

25

30

Fig. 3 Number of the AE signals in a series of tensile tests
with different tilt angles of the transducer.

should be noticed that first AE signals were detected atabout 0.5% strain regardless of the tilt angle of the transducer. This is consistent with the observation of cracks withthe optical microscope. For aU tilt angles. number of the
AE signals increased rapidly when the strain exceeded IS %at which the large number of delaminations had been observed with the optical microscope.

The formulation basically followed the transfer matrix
method described in Adler (1990) with an additional SO~
term, and was described in detail in Appendix. Constants
used in the calculation are listed in Table 1.
Table 1 Material constants used in calculation.
Material

From the experiment it is inferred that there are two different types of fracture of the SiOx coating. i.e.. cracks anddelaminations, and the directivity patterns of the AE radiation into waleI' are different for the cracks and delaminations.
Specifically. no acoustic energy is radiated from the cracks
into the direction normal to the specimen.
The number of detected AE signals from cracks increased with the tile angle of the transducer up to 35°. However, a quantitative determination of the radiation pattern is
not straightforward, because when the tilt angle was increased the distance from an AE source and the face of thettansducer rod increased and the attenuation and the diffraction loss in water also increased. At least. it might be correct that the radiation from cracks increased up to 35°.

x

e

PET

aJe (s 2/m)

water
PET

1.0
1.4

ISOO
2310

25 x 10-1'

1000

Figure 5 shows calculated results of the power spectra
as a function of the frequency and the radiation angle into
water. It should be noticed that no energy is radiated into thenormal direction when the force is for the crack. This isconsistent with the experimental result. And the intensity ofradiation from the crack model seems to increase up to 35°.
This tendency also agrees reasonably with the experimental
result.
On the other hand, in the delamination model. thepower spectra at different radiation angles are in the samerange of magnitude. This suggests that nearly same numberof AE signals are detectable with different tilt angles in theexperiment in the delamination strain range. This is consistent with the experimental results.

radiation
directionwater

Density
Velocity (m1s)
Attenuation(glcm3) longitudinal transverse constant::lN

Peaks in Fig. 5(a) and troughs in Fig. 5(b) correspondto the dispersion curves of leaky Lamb waves (Auld, 1990)
excited on a PET film loaded with water on one side.

vacuumFig. 4 A 2-dimensional model for the calculation.

4. Theoretical Model
Based on a simplified model of the experiment shownin Fig. 4, power spectra of AE signals radiated into different
directions were calculated. AE sources were assumed to be aline source distributed in Y-direction so that the model was
two dimensional in space. Each type of fracture was m0deled by:
For cracks; dipole type.
f j 5'(x) 5(z+d) 5(t),(f~=I. f, =f~ =0)(I)

For delaminations; monopole type,f j 5(x) 5(z+d) 5(t),(fs=f, =0, f. =I).

(2)

where d is the distance from the top surface to the line
source. d =+ 11.5 JIm was used for the calculation.

An experimental spectrum in Fig. 6(a) is the averaged
frequency spectra of waveforms detected in the experimentwith IS° of the transducer tilt angle in the strain range fromo to 9%, or the crack strain range. The spectrum was normalized by the method described in Nakaso and Yasujima(1993). It agrees reasonably well with the theoretical one atsame angle in Fig. 6(a) for the crack model. Therefore. theacoustic waves radiated from AE sources propagated in thespecimen as leaky Lamb waves and the energy leaked into
waterrAn experimental spectrum in Fig. 6(b) is the averaged
frequency spectra of waveforms detected in the experimentwith 0° of the transducer tilt angle in the strain range from24 to 30%. or the delamination strain range. It agrees wellwith a theoretical one at same angle in Fig. 6(b) for thedelamination model. Therefore, the AE source in case of thedelamination is satisfactorily modeled by the force in thenormal direction.

(a)......

~

Experiment0-!

c. -30 7
110
100

80

J;:

~Q~

60

'''3'~~'''' 40 20
~

0

_-20

=
:g,
I-

~ -30

(b)

&:

-. 30

.

~

~

-40~...&..--:!,=--o...;~:--, .......~_",",-~:---","""",::~

20

60

80

100

Frequency (MHz)

o

110

(a)

100
~~

80

"V~

60

~~.

~

40
20 0

Fig. S The calculated power spectra radiated into water. a)
A case of f. I. fy = f. = 0, for the crack model. b) A case of
C. = fy =0, f. I. for the delamination model.

=
=

-~
!
I-

PET films was investigated by experimental and theoreticalanalyses of acoustic emission (AE) signals recorded in tensile tests. Two distinctively different types of AE signals
were observed and identified to cracks and delaminations,
respectively. Although the cracks and delaminations wereobserved by the optical microscope in the present study,
optical observation would be extremely difficult when othermaterials are used for the coating or the coating is sandwiched by plastic films. In such cases. AE technique in thispaper is especially useful for the characterization of fracture.
To apply this technique to thinner glass coatings. effort isbeing made to improve the signal to noise ratio.

20

10
20

S. Conclusion

Fracture process of SiOx glass coatings deposited onExperiment

30

-~

120

Theory20;'" 10

&:

0
20

40

60

80

100

120

Frequency (MHz)(b)

Fig. 6 Comparison of spectra. obtained by experiment andtheory. a) A case of crack. b) A case of delamination.
References

Acknowledgment
E. Adler (1990), IEEE Trans. UFFC.37(6), 485-490.
The authors wish to thank Dr. H. Uyama and Mr. Y.
Koide of Toppan Technical Research Institute for the supplyof specimens and invaluable technical support. The authors
gratefully acknowledge Professor M. Takemoto of Aoyama
Gakuin University and Professor N. Chubachi of Tohoku .
University for helpful discussion.

Anon. (1992). "Silica-Coated Plastic Packaging", Food Processing. June, pp. 78-83.
B. A. Auld (1990). Acoustic Fields and Waves in Solids.
vol. 2. R.E. Krieger Publ. Co., Florida. pp. 63-104.

H, Kanai, No Chubachi and T. Sannomiya (1992), Acustica,
76, 199.
No Nakaso and H. Yasujima (1993), Jpn. J. Appl. Phys.,32, 2533-2535.

P. H. Wojciechowski and M. S. Mendolia (1992), "Fracture
and cracking phenomena in thin films adhering to highelongation substrates," Physics o/Thin Films, vol. 16, eds.
M.H. Francombe and Jo L. Vossen, Academic Press, NewYork.
Appendix

Based on the transfer matrix method (Adler, 1990), thepropagation of acoustic waves in a 2-dimensional model
shown in Fig. 4 is fonnulated. The substrate is an infinite
plate with a thickness h. The AE source is located in theplate, distance d from the top surface. The sources in cases
ofdelamination and cracking are modeled by a line force anda line dipole force, respectively. The top surface of the plateis in contact with a fluid. The calculation is aimed at o~taining the power spectra of acoustic waves transmitted into
the fluid with a definite angle of propagation.

-ik lt0A=where UI and u. are x and zcomponents, respectively, of thedisplacement vector, and G n and G,.. are zx and zz components, respectively, of the stress tensor in the substrate. We
take an angular spectrum of each component with a definite
value of kI , which is an x component of the wavevector.
Harmonic dependency on time with an angular frequency CJ)
is assumed. This corresponds to measuring a wavefonn of aplane wave component propagating in the fluid with anangle of direction 9 = sinOI(c,..kJro) where c.., is a soundspeed in the fluid, and taking a Fourier transform of the
waveform.
With these assumptions, the partial differential equation
for the wave propagation in the substrate can be reduced to aset of first-order ordinaI)' differential equations in a matrix
fonn (Adler, 1990),
dXldz = AX - f 8(z+d).

2
2
CI -2c I

0

c?

2
2
2
P( 4crk~ c I ~ c t _ro )0r is a force tenn which takes the fonn
fa.ct = (0, 0, ileaf., 0)1 for cracking andfddami = (0, 0, 0, fa>' for delamination.

I

pc~
0

z

=eAzC +

JeA(z-~)f S(d + l;)dl;,

0
1

pc?
2
2
_Ok c, - 2c t
0
0
I x
2
c,
_PCil 2 -ik x
0

(8-4)

-h

(a-3)

2

~i

Here p is the density of the substrate, and Ct and Cl are longitudinal and transverse velocities respectively of the su~
strate. The solution of (a-2) is,
X(z)

(a-2)

f. and f. are strengths of the sources. The matrix A is

Let us define a four dimensional vector,

-ik x

(a-I)

k z = -2-- k
Cwwhere the superscript and subscript w stand for the variablesin the fluid. T is a transmission coefficient at the fluid! substrate interface which should be determined by the boundaJy
conditions. At the fluid/substrate interface where z = 0,

where C is a four dimensional vector which should be 0,..
termined by the boundaI)' conditions.

(a-6)

and
The four dimensional vector for the acoustic wave inthe fluid is simply written as
XW=(u:' u~ G~ G~)t

= T eiltzz(k x k z 0 iPwCil2)1,

(a-7)

=

At the bottom surface of the substrate where z -h,
(80S)

X(-h)

=e- C.
All(a-8)

Combining (a-6. 7. 8) with the boundary conditions

=

=

=

0, Ou 0 (z -b),u.' on' 0 .. are continuous (z = 0),

0 ..

(a-9)

we obtain a matrix equation as follows;

H31
H41
0
0
0

H32
H42
-1

H3 3
H43
0

0

-1

0

0

H34 0
H44 0
0
kz
0
0
-1 iPwCl)2

C1
0
C2
0
C3 = D23 f3 + D24 f 4C4033 f3 + D34 f4T
043 f3 + 044 f4

where Hi; and 011 are ij-components of matrices H and 0
respectively. Here, H 5! e·Ab and D is eAd • Solving this equation, the coefficient T. and hence the arnpliwde of the harmonic plane wave in the fluid. are obtained.
To take into account the effect of acoustic attenuationin the fluid, a very simple model is employed. T is multiplied by an attenuation factor exp(~). a.. is the attenuation coefficient in the fluid, and 1=1(9) is a mean distance
between the surface of the substrate and the face of thetransducer (See Fig. A-I).
The above scheme was implemented with Mathematica(version 2.2. Wolfram Research. Inc., Champaign, Illinois,1993) on a Macintosh computer. and iterared with different
values of k. (hence 8) and CI). The results are shown in Figs.
Sa and Sb.
Ccnler axis of
the aansducerz+

Transducer
face ~

Rd .'

.:"-0

...

~

.tt

'

water
x

PET

.~ source

Fig. A-I The mean distance. 1(9), was introduced by, 1(9) =(r.+R,I2sin 8)1cos 9. Rd and r. took values of 8 mm and I
mm, respectivily.

(a-l0)

Future Meetings on AE
Fifth International Symposium on Acoustic Emission from Composite
Materials, July 10·14, 1995, Sundsvall, Sweden
See page 199 ofVoJ. 12 (3/4) for preliminary program listing. Proceedings will beavailable at the time of the Symposium. For more information, write to
Ms. Tina O'Donnell, ASNT Conf. Coodinator
ASNT, PO Box 28518, Columbus, OH 43228-0518
Phone 614-274-6003; FAX 614-274-6899

22nd European Conference on Acoustic Emission Testing, incorporating
EWGAE, May 29-31, 1996, Aberdeen, UK
For more information, write to
Meg Thain, Conference Organizer
The Robert Gordon University
Kepplestone, Queens Road, Aberdeen AB9 2PG UK
Phone (44)-1224-263322; FAX (44)-1224-263323
e-mail: m.thain@rgu.ac.uk

The 13th International AE Symposium (IAES 13), November 27-30, 1996,
Nara, JapanFor more information, write toProf. Y. Higo, Program Chairman
Tokyo Institute of Technology, 4259 Nagatsuda, Midori-ku
Yokohama 227, Japan
Phone (81)-45-922-1111, x2044; FAX (81)-45-921-0898

The 6th Conference on AEIMS in Geologic Structures and Materials, 1996
(date to be decided), at Pennsylvania State University
For more information, write toProf. H.R. Hardy, Jr.
110 Hosler Bldg, The Pennsylvania State University
University Park, PA 16802
Phone 814-863-1620; FAX 814-865-3248

14th World Conference on Non-Destructive Testing, December 8-13, 1996,
New Delhi, India
For more information. write to
Dr. Baldev Raj, President, International Committee on NOT
Director, Metallurgy and Materials GroupIndira Gandhi Centre for Atomic ResearchKalpakkam 603102, Tamil Nadu, India
Phone (91)-4117-301/356; FAX (91)-4117-360
e-mail: dmg@igar.iitrn.ernet.in
3J

On Characterization and Location of Acoustic Emission
Sources in Real Size Composite Structures •A Waveform Study
M. A. Hamstad and K. S. DOWDS
Abstract

structures seeks to answer three key questions for each AE
signal. Ideally one wants to determine the significance, thelocation, and the source type for each detected AE signal.
During an examination (Hamstad, 1992) of a large share of
the literature dealing with AE from aerospace composites, it
was observed that nearly all the fundamental experimental
studies relating to significance, location. and source typewere based on relatively small coupons and/or beams where
the sensor was quite close to the AE sources. Fundamental
studies, as defined in this paper. are those that emphasize
instrumentation such as wideband, small aperture, flat-withfrequency sensors coupled with wide-dynamic-range wavefonn m:ordets for studies dealing with different AE source
mechanisms and AE source identification. For typical NDE
evaluation of fiber/polymer composite structures, the AE
source-ta-sensor distance is considerably larger. Thus, one
might ask. how does the additional wave propagation distance change the ability to evaluate the significance, location, and source type of the strueture-generated AE signals?
Can the so-called near-field (Lamb waves) AE characteriz.a.
tion results be extended to the far-field (Lamb waves) data?

A series of pairs of acoustic emission (AE) wavefonns
taken from either a closely spaced pair (64 mm) or a widely
spaced pair (410 mm) of AE sensors mounted on a sphericalgraphite/epoxy pressure vessel of 260 mm outside diameter
were examined. The wavefonns from the small (6.3 mmdia.) apertUre non-resonant sensors bandpassed from 85 to
325 kHz were recorded simultaneously on a 12-bit waveform recorder. Changes due to wave propagation in the typical AE hit characteristics (peak amplitude, duration, energy,
spectrum, etc.) were correlated with distances from source tosensors and physical principles of wave propagation. Baged
upon the results, implications for AE monitoring and future
AE studies of large fiber/polymer composite structures arepresented. Also, AE source location in conjunction with amodel for localized failure of a large aerospace type fiber/polymer composite structure was considered. Large changes
in typical AE hit parameters were observed, particularly inthe first 60 mm of propagation. These results bring into
question typical approaches that have been developed forsource identification and assessment of source significancein small test specimens. Large changes in arrival times ofthe same event at separate sensors were observed as a function of the system threshold setting. Possible approaches toovercome arrival time deficiencies as well as suggestions for
future studies are presented.

The purpose of this paper is to address the above ques.tions based upon AE waveforms taken from pairs of nonresonant AE sensors mounted on a fiber/polymer composite
pressure vessel. The pairs of small aperture sensors wererelatively closely spaced in some cases and widely spaced inothers.

1. Introductionz. Test Vessel Construction

The application of acoustic emission (AE) technology
to fiber/polymer composites continues to be one of the key
successes of AE technology. These applications span therange from small coupon or small beam test specimens tolarge structures, such as chemical processing tanks and pipelines. The evaluation of AE signals detected during n0ndestructive evaluation (NOE) of fiberlpolymer composite

Aerospace-type graphite/epoxy pressure vessels wereconstructed on a linerlmandrel consisting of two 5083 aluminum alloy hemispheres 1.3 mm thick which were gas
tungsten arc welded at the equator. Each welded liner wasadhesively bonded to two aluminum alloy bosses. A nominal 4.6 mm thick composite wall was filament wound withgraphite fiber (Amoco T -40) preimpregnated with epoxy,with a final matrix weight fraction of approximately onethird. One of the two bosses was monolithic, whereas theinlet boss had an internally threaded port opening. Figure I
shows a cross section of the test vessel. Because the mosttypical failure scenario for a nominally manufactured vessel
is to rupture near either one of the two bosses, the entire
AE test scheme concenttated on these two areas for gathering and analyzing AE activity. Sixteen AE sensors were

Received 26 May 1995. M. A. Hamstad is affiliated with ~panment of Engineering, University of Denver, Denver, CD
80208 (mhamstad@du.edu) and K. S. Downs is with Lockheed
Martin, P.O Box 179, Denver, CO 80201 USA. This work wassponsored by Manufacturing Technology Directorate. WrightLaboratory, Air Force Materiel Command (ASC). United States
Air Force, Wright-Patterson AFB, Ohio 45433-6533 and by
University of Denver.
Journal of Aeoustic: Emission
Volume 13, Numbers 1/2

3f

0730-00S0J9SJSS.0Q(13031-13041
Copyri_I99S Acoustic: Emission GroupAE
Sensors

Boss with inlet port
(North Pole)

>

E

8

3a

4

Q)

"0

~
1S.

0

<

E

-4

.a
800

:>

E

3b

400

Q)

"0

::J
:!::

0

1S.
E
< -400-800

Monolithic Boss
(South Pole)-Fig. 1 Cross section of typical test vessel.

~

a:

-10

I-

-20

.

en

en

Z

0

-30

~

-40

0

-50

Q.

;;

as

a:

m

"

o

-SO

50
100
Time (microseconds)

150

-60
0

100 200 300 400 500 600 700

Frequency (kHz)Fig. 3 Waveforms and response from PZT sensors relativeto NIST·SRM conical sensor each at 0.254 m from a pencil break on an aluminum plate (gain = 0 dB): (a) PZT
sensor: bandpassed 85-325 kHz; (b) NIST-SRM wideband
sensor; (c) Spectrum ofPZT sensor relative to NIST-SRM
sensor.
locations of the three sensors of interest. The nearer pair ofsensors (#1 and #9) had a separation spacing (along the vessel exterior surface) of 64 mm; the widely separated pair ofsensors (#9 and #15) had a spacing of 410 mm.

Fig. 2 Relative location on the test vessel of the thnle
sensors of interest (#1. #9. #15).

3. Test Hardware

ammged in two concentric rings around each boss (foursensors in each ring). The wavefonns presented here weregathered in pairs from three of the sixteen sensors: sensor#1 (49.70 north latitude. 6()0 longitude), sensor #9 (60.80
north latitude, ISO longitude) and sensor #15 (60.8 0 south
latitude. 195 0 longitude), where longitude angles are given
in degrees clockwise from a filament winding feature whenviewed from the North Pole. Figure 2 shows the relative

A special proof test fixture was created to maximize AE
test repeatability. Further details on the uniqueness of thisfixture are described in Downs and Hamstad (1995a). The
Staveley lead zirconale titanate (PZ'I) sensors used to gather
the waveforms presented here were wideband, non-resonant
sensors with a nominal case diameter of 9.5 mm; their aper
32

ture is small (6.4 mm dia.). and they have a displacement
response which is fairly flat with frequency. These pzr
sensor outputs were bandpass filtered with -3 dB points at
approximately 85 kHz and 325 kHz. The PZT sensor response was compared to the response for a National Institute of Standards and Technology - Standard Reference Material (NIST-SRM) sensor by performing a pencil lead break
0.254 m away from each sensor mounted on a large. 3.1mm thick aluminum plate. Figures 3a and 3b show theresulting waveforms from the lead breaks for both a pzr
sensor and a NIST-SRM sensor. Figure 3c shows the spectral response of the PZT sensors relative to the flat-withfrequency conical NIST-SRM sensor.

500 - , - - - - - - - - - - - - - ,

4a

~
G>

~

0

t -250-500 -t--.---+--r--r--r--r.......-.--.....-,..-.....--!

500-,------------.....,

4b

:>

250-

- o
E

Waveforms from naturally occurring AE were obtainedusing a 12-bit digital wavefonn recorder (10 megasamples
per second). The waveforms were recorded simultaneously(i.e.• one trigger penetration triggered both channels) fromone pair of sensors at a time. either the near pair (#1 and #9)or the widely separated pair (#9 and #15). and were stored on
disks for subsequent processing.

250

~

:s

::

t

-250-

-500 +-......"""T--.,,.....,.......--,r--...................--r--.-i
100 - , - - - - - - - - - - - - - - - .

4c

4. Far-Field vs. Near-Field AE in Composites:>.5.

In order to discuss key aspects relating to near and far-

G>
"C

field AE in fiber/polymer composites. a series of pairs ofwaveforms will be presented and discussed. These wavefonn pairs were collected during the proof testing of thegraphite/epoxy pressure vessels. These vessels had an outersurface area of about 0.21 m2• which is some 175 times the
typical single-side surface area of a tab-type tensile composite sample (e.g.• 12 mm x 100 mm).

::

Each pair of waveforms presented throughout this paper
is known to have resulted from a single AE source event
This fact was carefully established based on several observations. First, the waveform pairs were recorded almost exclusively during Felicity ratio loading or well into holds atconstant pressure. Thus. event rates were quite low. Second. the typical time periods between events and between
hits from one event were typically observed to be of cfiffefent orders of magnitude when the hit listings of the resultsfrom all sixteen sensors used in these experiments werestudied. Third. each wavefonn was recorded on a 12-bit
wavefonn recorder with a window of approximately 800 J1S
and with the trigger set near the cennal portion of the window. If the two recorded hits had in fact been the result of
two different events (rather than the presumed single event).
the 12-bit data would have had sufficient resolution to allow
detection of the later arrival for a reduced-amplitude second
hit at each of the two sensors. The wavefonns presented
here were examined to see if any such second hit arrivals
occum:d, and no plausible hits consistent with an assumption of two different events were detected. Fourth. in allcases the second hit recoRIed from the sensor pairs was
lower in peak amplitude and was more dispersed in time.

:s
1S.
E

<

50

o
-50

-1 00 -t-....---,-....---,-....---,--r-..,....~..,.....,........j-100 0100 200 300 400 500
Time (microseconds)
Fig. 4 Waveforms from sensors #15 and #9 (spaced 410
mm apart) for a single graphite/epoxy AE event originating
very near sensor #15 (gain 40 dB): (a) Sensor #15; (b) Sensor f9 with same vertical scale as in (a); (c) Sensor f9 withenhanced vertical scale.
This behavior is consistent with the two hits in each wave-

fonn pair having occurred from a single source event. Finally. considerable experience in interpreting waveformpairs had been gained from previous waveform recording of
single lead breaks located at various points on the pressure
vessel.

Figure 4 illustrates a pair of wavefonns for one particular AE event simultaneously recorded by the two widelyspaced sensors: Figure 4a is from sensor #15; Figures 4band 4c from sensor #9 show a single wavefonn with two
different voltage scales. The two waveforms recorded forthis event are particularly interesting because the AE event
originated very near one of the two sensors. specifically#15. The reasons for concluding the closeness of the originof this event to sensor #15 will be apparent in the cumulative discussions which follow. The fust observation to be4.0-r------------.....,

~

CD

3.0

'g

2.0

ci

1.0

:=
Q.

0.0 -F==;;.--,.-..--.,.-.......""""T-,..--.,...--r---\
1.0

~

0.8

~

0.6

::I

~
E
<I:

0.4

0.2
0.0 4=;::;..

o........,......-,----t=~-t

--,~

100

200

300

400

500

Frequency (kHz)Fig. 5 Spectra (FFI) of wavefonns for waveform lengths
shown in Fig. 4: (a) Sensor #15; (b) Sensor #9.

made is the large difference in the peak amplitudes of thetwo sensor hits from the same event The peak amplitude
drops from 484 mV for sensor #15 to 73 mV for sensor #9,
a drop in peak amplitude of about a factor of five. The second observation is that the character of the wavefonn at thesecond hit sensor (#9) has the typical form of that observedwith wideband, flat-wi~frequency sensors on a thin plate,namely a low amplitude extensional wave packet followed
by a flexural wave packet with a slower group velocity.
This characteristic, which is distinctive of a far-field AE
wave in a thin plate (prosser and Gorman, 1992), is notpresent in Fig. 4a for the first hit sensor (#15). Third, there
are a number of other large differences in terms of the normal parameters which are typically used to characterize AE
hits in commercial AE instrumentation. The rise time andthe hit duration are both much longer for the second hit
sensor (#9). A numerical calculation of the energy in the
waveform from each hit shows that the energy level for thesecond hit sensor (#9) is down by an order of magnitude
compared to the ftrst hit sensor (#lS). Figure 5 also showsa substantial difference in the Fast Fourier Transform (FFT)
spectral content of these two hits from the same event. At
the second hit sensor (#9), the frequency content is shiftedmuch more towards the lower portion of the frequency band.
The data base that has been assembled for small specimens with near-field sensors (e.g., Ely and Hill, 1992) implies that the variations in the hits recorded at the two sensors (Le., Fig. 4) resulted from two different AE source
mechanisms. That is, the present small-specimen data base
implies that traditional AE measurements (such as peak

amplitude, duration, rise time, energy, etc.) can be usedeither singly or in concert to distinguish different source
mechanisms. However, using the present small-specimen
data base to conclude that the two hits shown in Fig. 4 resulted from two different AE source mechanisms contradicts
the fact that these two hits resulted from the same event.
Further, since the measured values of AE peak amplitude
have been used to determine the relative level of damage
represented by an AE event (CARP, 1987), the above results indicate that applying the small specimen data base tofiber/polymer composites of real structural sizes for the
purpose of determining damage levels from measured peak
amplitudes cannot be done in a straight forward fashion.
Thus, the results presented here are strong evidence that thesmall-specimen data base must be applied with great care(and perhaps not at all) to far-field, large composite structures for either assessing damage level via measmed peak
amplitudes or for attempting to distinguish source mechanisms.
Figures 6 and 7 show an opposite case (in reference toFigs. 4 and 5) for the widely-spaced sensors (#9 and #IS).
In this case, rise time, peak amplitude, duration, energy,
spectral content, etc. are very similar for the hits at the two
sensors from the same AE event. It was concluded that the
AE source in this case was located in the far-field at approximately the same distance from each of the two sensors.
This conclusion was based upon the nearly equal arrival
times and the almost identical time-lengths for the extensional portions of the waveforms. The implication of thisresult is that it might sometimes be logical to use the traditional parameters to attempt to distinguish between AE
source mechanisms, but only for those limited cases inwhich the locations of both the AE source events and thesensor(s) are fixed with respect to one another.
Attention will now be turned to event wavefonns ga~
ered simultaneously from the two near sensors (#1 and #9).
Figures 8 and 9 show a very similar case to that seen in
Figs. 4 and S. i.e., where the AE event originated very near
one of the two sensors. The peak amplitudes vary by 14 cB
for the two sensors hit by the same event (Fig. 8). Clearlymost of the other traditional AE parameters vary as well
between the fIrSt and second hit sensors (#1 and #9). but not
all of these parameters vary by the same ratios as for the
more widely spaced sensors (#9 and #15). For example, thedurations of the main wave packet are about the same forthe near pair, whereas they were significantly different for
the widely-spaced pair. Also, the calculated energy ratio
decreases by afaetor of 15 between the fust hit sensor (#1)
and second hit sensor (#9) of the nearer pair (versus an"apparent" decrease of a factor of 10 for the widely-spaced
sensors, as seen in Fig. 4). This "apparent" decrease inenergy for the widely-spaced sensor pair (vs. the near pair)warrants fuJ1her explanation. Each sensor on the sphericaltest article can receive a signal from a single AE source
event from two different directions: (a) along the most dj.

500-------------..

5.0-r------------..

~

~ 250

~
~

-

o

4.0
3.0
2.0

Co

<E -250

1.0
0.0 -r;;~--r--r__....--"'T"""_,_~~__I
5.0-r-------------.,-500 -I-_~..,.__r__r__r_,__.,._,__,_...__i
500~-------------,

:>

.s

250

-g

0

:>

-

7b
4.0

E

Q)

3.0

~

2.0

~ -2501.0Q.

-500 -I-_-100

0.0 -F"=-r---r-.,..-..r--__..,....~.....,..~__I
o 100 200 300 400

500_r_....,..&_r_....___r_...-,_....-~...__i

0

100

200

300

400

500

Frequency (kHz)Time (microseconds)

Fig. 7 Spectra (FFT) of waveforms for wavefonn lengths
shown in Figure 6: (a) Sensor #15; (b) Sensor ##9.

Fig. 6 Wavefonns from sensors #15 and ##9 (spaced 410
mm apan) for a single graphite/epoxy AE event originating
approximately equidistant from sensors #15 and ##9 (gain
40 dB): (a) Sensor #15; (b) Sensor ##9.

cant extensional portion of the waveform;(c) both first hit sensors have substantially greater peak
amplitudes versus the second hit sensors;(d) the spectral content of both hits from the lead break(Fig. 11) are similar to each other;(e) the spectral content of both hits from an actual AE
event (Fig. 9) are similar to each other; and.
(f) the amplitude of the spectral content is reduced forthe second hit sensors versus the flTSt hit sensors.

reet path between source and sensor and, (b) from around theother side of the sphere. Usually the hits received by a single sensor for a single event from these two directions havea sufficiently different arrival time so as not to superimpose
in a significant manner upon each other. However, in thecase of a sensor located approximately 1800 or so away froman AE source (where the two paths of travel may not besignificantly different in length). superposition of the two
waves can occur in such a way that some traditional AE
parameters (e.g., energy content) have greater measuml values than they ordinarily would have.

The reader should make an additional observation Iegarding Figs. 8 and 10 as contrasted with Fig. 4. In Figs. 8
and 10, the second hit sensor does not show the first arriving extensional wave packet of distinctly lower amplitude
that is present in Fig. 4. Typically. weJl-developed extensional and flexural wave packets are present for propagation
distances greater than about 15 times the plate thickness(Weaver and Pao, 1982). Because the pressure vessel wall
total thickness is on the order of 6 mm, the Lamb waves
have not fully developed in Figs. 8 and 10 since the waves
have only propagated a distance of about 64 mm.

On the other hand. the spectral disbibution (see Fig. 9)
is similar for the two near sensors (#1 and ##9), although it
is significantly reduced in amplitude at the second hit sensor(##9). Again. the reason for the significant changes in the
wavefonns from a single source event detected at two sensors is due to the fact that the AE event originated very
close to one of the two sensors. specifically sensor # I.
This result was verified by perfonning a lead break on thevessel surface very near sensor #9. Figures 10 and 11 forthe lead break near sensor ##9 show strong similarities with
the information in Figs. 8 and 9 for an actual AE event
originating near sensor#!. Specifically. some of the similarities are as follows:(a) both first hit sensors do not exhibit any extensional
portion of the waveform;(b) both second hit sensors do not exhibit any signifi-

It should also be noted that a shon distance (such as 64mm) from an AE source to the sensor is often present insmall tab-type samples. In such samples. results similar to
those shown here have not been reported earlier possibly due
to two primary reasons. First, the usual experiment has
only one sensor. Second. very early edge reflections of the
wave packet make it more difficult to understand the resulting waveform.
35

30

:>

E
Q)

20

'0

:;,

=
0.
E
<:

10

o -I=::,.....~.....--r-.....-~~;:::::~
10 - - - - - - - - - - - - - - - ,

~

-

8
6

4

2
O-P=~__._o_____.~T_.,.__~~-=t

100

200

300

400

500

Frequency (kHz)Fig. 9 Spectra (FFI) of waveforms for waveform lengths
shown in Fig. 8: (a) Sensor #1; (b) Sensor #9.
event occurs very near one sensor, three primary observations can be made:(a) the spectral content for the first hit sensor displaysa range of frequencies (including a non-trivial fraction ofhigher frequencies) and has a fairly high average frequency(e.g., greater than 200 kHz) as seen in Figs. Sa and 9a;(b) if the second hit sensor is in the near-field (e.g.•
Fig. 9b for the near sensor pair), the shorter propagation
distance results in a spectral content for the second hit sensor that is similar in range and distribution to that for the
first hit sensor, although the amplitudes are all reduced; and.
(c) if the second hit sensor is in the far-field (e.g.• Fig.
5b for the widely-spaced sensor pair). the greater propagation distance causes the higher frequency content of its spectrum to be dramatically reduced, thus resulting in a lower
average frequency (e.g., less than 200 kHz) and a spectral
distribution that is very different from that of the first hit
sensor.
For the case in which an AE event occurred in the far-fieldapproximately equidistant from each of the sensors (e.g.,
Figs. 7 and 13), two observations can also be made:(a> the spectral content of the flJ'St hit sensor generally
matches that for the second hit sensor in tenn of frequency
range, distribution. and amplitudes; and,(b) the average frequency is rather low (e.g., less than
200kHz).

-1.0 +--r-~'-r-""'T"".....,..-.,.........---r---r~r--r---i-100 0100 200 300 400 500
Time (microseconds)
Fig. 8 Wavefonns from sensors #1 and #9 (spaced 64 mm
apart) for a single graphite/epoxy AE event originating very
near sensor #1 (gain 40 dB): (a) Sensor #1; (b) Sensor #9
with same vertical scale as in (a); (c) Sensor #9 with enhanced vertical scale.
Just as with the widely-spaced sensors, the wavefonns
at the two closely-spaced sensors can be nearly identical.
Figures 12 and 13 show such a case where the AE hit parameters are almost identical for hits at sensors #1 and #9.
As before, the nearly identical arrival times and equal timelengths of the extensional wave packets indicate that thesource was about the same distance away from each of thesensors and was in the far-field; i.e., at a distance greaterthan about 15 times the plate thickness.
The explanations of the key featmes of the wavefonns,
which have been described above, depend on four key physical principles. First. a polymer-based composite possesses
frequency-dependent material attenuation. The result of thismaterial attenuation becomes especially apparent when one
considers the variations in the spectral content of the signals
received by different sensors. For the case in which an AE

A second key physical principle to consider is that geometric spreading is present for all AE sources. This phenomenon accounts for the large loss in amplitudes for relatively short propagation distances when one sensor is very36

40,..---:------------,

4.0

11a

10a

:>

§.

2.0

30

CD

0.0
-2.0

20

j

10
o~-,L-.........,.--,~--...............-::=::;::==;:~
5.0-r--------------.

-4.0
4.0

10b

:>

4.0

~
::::l

3.0

E

2.0
0.0

~

.....~,.....,.

-

==
Q.

2.0

<

1.0

E

-2.0

0.0 +=:*"-.........,.--,~~..,...;::=;-...........--1
o 100 200 300 400 500
Time (microseconds)

U)

-4.0
0.3
0.2

-

0.1
0.0

Fig. 11 Spectra (FFT) of waveforms for wavefonn lengths
shown in Fig. 10: (a) Sensor #9; (b) Sensor #1.

:=
Q.

-0.1

the material attenuation which continues to cause losses inamplitude.

-~

CD
'C
::::l

10c

E

< -0.2
-0.3
-100

0

100

200

300

400

500

Time (microseconds)
Fig. 10 Wavefonns from sensors #1 and #9 (spaced 64 mm
apart) for a single graphite/epoxy lead break performed very
near sensor #9 (i.e., 1.5 rom from sensor case edge) (gain
40 dB): (a) Sensor #9; (b) Sensor #1 with same verticalscale as in (a); (c) Sensod#J with enhanced venical scale.
near the AE source, as is seen in Figs. 8 and 10. This
spreading loss has two components:(a) IIr losses, which govern the propagation when thespherical wave spreads throughout the structure thickness,and (b) 1I"r losses. which govern the subsequent wave
propagation when the circular wavefront spreads over thesurface area of the test structure (where r is the propagation
distance in both cases).
For the current thin walled structure, only the ciR:ular
spreading is relevant. For circular spreading from r = 6.4
rom (approximately the vessel wall thickness) to r = 64 mm
or to r = 410 mm. the losses are 10 dB and 19 dB. respectively. These circular spreading values are of the same orderas those observed in the sensor pair data presented here. As
the circular spJeading continues. it is not as significant as

Third, for longer distances of propagation in plate arxf
shell-type geometries. the characteristic waveforms are thoseto be expected from Lamb waves. The two primary modes
are extensional waves of higher group velocity followed byflexural waves of lower group velocity with higher amplitudes. This expected behavior accounts for the differences
seen between Figs. 4 and 8 where in both cases the AE
event originated very close to the first hit sensor. In Figure
4 (for the widely-separated pair). the second hit sensor is far
enough away from the AE source for full development of
the Lamb waves; in Fig. 8 (for the near pair), however. thesecond hit sensor is not far enough away from the origin of
the AE event for Lamb waves to have fully developed.
Fourth. the Lamb waves are dispersive waves (i.e.• thegroup velocity depends on frequency.) Thus, the wave energy spreads out in time with increasing propagation distance. Also, the time difference between the initial arrivalof the extensional wave packet and the subsequent arrival of
the flexural wave packet increases with greater propagation
distances. For example, Fig. 12 (for the near sensor pair)
has a shorter time difference between the initial extensional
arrival and the flexural arrival (about 58 JIS) versus Fig. 6(for the widely-separated pair) which has a longer time difference (about 80 j.lS).

8.0...,.-------------.,
~

~

4.0

CD

0.0

E
ct

-4.0

~
Q..

2.0

12a

1.0

-

o.o-+--""""'~

J!l

~

-1.0

0.0 .....-

4.0

-1.0

0.0

-2.0 +---r---r--:,.--,r--.,....-.-~__r......,.__t
-150
-50
50
150
250
350
Time (microseconds)

1.0

::J

:=

Q..

E
ct

Ii)

-8.0 +--.--r--+-_,_--r-.....,.......,.......,._......,~,....-f
8.0"T"""-------------,~-r--------------,
i)
14a

-4.0

-8.0

1.5
+--.-~-I-_,._

-100

0

.......

100

200"""""'--r-__t

300

400

500

~

o

Time (microseconds)z:..

Fig. 12 Wavefonns from sensors #1 and #9 (spaced 64 mm
apart) for a single graphite/epoxy AE event originating approximately equidistant from sensors #1 and #9 (gain 40dB): (a) Sensor #1; (b) Sensor #9.

.......

-r--------------,

1.0
0.5
0.0
-0.5
-1.0

1.0
0.5

Ii)

0.0 -+--"lIlMIl

-0.5
-1.0
-1.5 +-~

100 . . . , . - - - - - - - - - - - - - - ,

13a

~

--g

75

-150

Q)

:=

50

Q.

~

25
_

o ~~--r---r-__r__..___,r__r=.:;_.....""'"~~

100 .......- - - - - - - - - - - - - ,

>E

-

-50
50
150
250
350
Time (microseconds)
1.5..,.------------.,
14c
1.0
0.5
0.0
-0.5
-1.0
1.0 Ii)0.5
0.0 -t----fI4WIl.....
-0.5
-1.0
-1.5 +---r---r--..--,r--.r--.---__r-__t
-150
-50
50
150
250
350
Time (microseconds)

75

Q)

"C

::J

:=

50

Q..

E

ct

r---r-_,__-,_.....___r-r__t

25

o

100

200

300

400

500

Frequency (kHz)

Figure 14 (a-c) Three pairs of wavefonns. with each pairarising from a single graphite/epoxy AE event and poten-

Fig. 13 Spectra (FFI) of wavefonns for waveform lengths
shown in Fig. 12: (a) Sensor #1; (b) Sensor #9.

tially showing different types of source mechanisms: (i)sensor #15 and (il) sensor #9 (spaced 410 mm apart) (gain

40 dB).

3B

s. Wave Propagation Implications for Developmental Studies on Large Composite Structures
For large composite structures which have plate orshell-type geometries, there are several implications basedon the above results with respect to some of the researchthat needs to be undertaken. First. daIa and numerical roodels need to be developed to characterize the dependence oftypical AE hit characteristics on the distance of propagation
for different bandpasses and various thicknesses of fiber/polymer composites. These daIa are of key importance tothe process of making rational decisions about AE sensor
spacing for large composite structures. Because of the highcost of using large numbers of sensors. the sensors must be
spaced as far apart as is feasible. Since geometric spreading
effects are always present, the only means to reduce thenumber of sensors required is to lower the bandpass. In thisway, one can monitor those (lower) frequencies experiencing
a lesser degree of material attenuation and take advantage ofthe higher amplitudes which are present in the flexural mode
at lower frequencies. It is important to note that the sensor
system must have equal or better sensitivity at the lower
frequencies (as compared with the sensitivity at the higher
fn:quencies) for this approach to be effective. Also. thethreshold must be reduced to overcome the high initial signal losses (approximately 14-24 dB in the fIrSt 60 mm ofpropagation) (Downs and Hamstad. 1995b) that occur for all
the AE events due to geometric spreading (unless. of course.
a sensor is directly above the source event).
Second. an approach needs to be developed to flag AE
hits for which the event characteristics were determined in
the near-field where the event characteristics are changing at
a very high rate. Third. a means must be developed tomeasure and utilize the distance an AE signal has uaveled
prior to measurement by an individual sensor. Without
such an approach, the typical event characterization is often
meaningless. It may be possible to combine wideband, flatwith-frequency sensors with a series of multiple-level thresholds (starting from just above the noise level) to obtain awhole series of anival times for each hit. Such a scheme
may allow calculation of the necessary time difference between the arrival of the extensional wave packet and theflexural wave packet. Then using the typical initial groupvelocities of these two packets. an approximate range fromthe source could be calculated, and this information could be
used with the data obtained as described above to adjust themeasured hit parameters to a constant propagation distance.
Fourth, studies need to be made to determine if far-field
waveforms in fiber/polymer composite plates contain sufficient information to differentiate between types of sources.
Since the study presented here was not as wideband as isdesirable (say. 30 kHz - I MHz). the current data are somewhat inconclusive. Nevertheless. Figs. 14a. 14b. and 14ceach show a pair of waveforms from the widely spaced sensors (#9 and ##IS). The two hits within each pair seem tohave a similar character; however. each of the three pairs has

a different character compared to the other pairs. where thecharacter difference is not attributable to the source being
located very near one of the sensors. The variety of character evident in these waveform pairs implies that it may be
useful to study whether it is possible to differentiate source
mechanisms from far-field waveforms in composites.
6. Wave Propagation and AE Source Location in
Large Composite Structures
Before discussing AE source location. it is important toconsider a possible model of stress-induced damage in fiber/polymer composite structures.
(1) Microdamage begins at relatively low percentages ofthe failure level. For example, in a graphite/epoxy composite structure under biaxial stressing. considerable AE is easily recorded starting at 10-15% of the ultimate failure levelof the structure. as occurred in the pressure vessels studied
here.
(2) When a composite structure is loaded in biaxial
stress. each increment of additional stress results in an increase in the relatively uniformly distributed "characteristic
damage state" of the composite (Reifsnider and Masters.
1918).

(3) Failure of a composite structure is not primarily dl>termined by the "characteristic damage state." Instead. failure typically is the result of a higher concentration of damage accumulating in a localized zone of the structure.
(4) In a composite structure. the localized zone of concentrated damage often occurs at geometric stress concentrations in the structure. and typically there is more than one
such zone in the structure. Further. even at a single geometric stress concentration, there may very ~ell be morethan one localized zone of growing concentrated damage.
(5) The number of AE events resulting from the generation of the "characteristic damage state" is typically ordersof magnitude greater than the number of events comingfrom the zone of localized, concentrated damage in a weUdesigned and fabricated composite structure.
Based upon the above model, it does not make sense toattempt to use AE to cany out nondestructive evaluation
relating to the failure strength of a composite structure unless accurate track is kept of the source locations for the AE
events which are sensed and recorded. If source location is
ignored. then the AE from the generation of the "characteristic damage state" will confuse the daIa analysis since it
is much more numerous than the number of AE events
coming from a loc:alized zone of concentrated damage.
Also, if AE from different zones of concentrated damage is
not distinguished. the data analysis will be confused. In thediscussion that follows, it is assumed that AE event rates
are not so high as to preclude source location. That is, theevent rates have been controlled by the use of a combinationof low stressing rates. hold tests. andlor Felicity ratio typesof test-load profiles.

Typical commercial AE measurement systems use afixed electronic threshold to determine hit arrival times andthe arrival sequence of the hits generated by a single AE
event. Using the wavefonns in Figs. 4 and 6. the differencein the arrival times for the hits at the two widely spaced
sensors (410 mm apart) were determined for various threshold levels at 3 dB increments (to simulate different AE
source amplitudes or differences in the distance from thesource to the sensor) for a two-sided threshold (i.e., thethreshold could be penetrated for both the positive and negative voltages). These arrival time differences are plotted inFig. 15. Clearly there are wide variations in the time differences for the various thresholds. which will result in poor
location accuracy. For the data shown here. the arrival timedifference is up to a factor of 2.5 for the event originatingclose to one sensor (Fig. 4), and up to a' factor of 12.6 forthe event originating approximately equidistant from eachsensor (Fig. 6). These wide variations were not isolatedcases; a dozen other randomly selected pairs of hits wereanalyzed in the same way, and each had similar wide variations in the arrival time differences. With a high sensor density (i.e., a small average value of total surface area of com·posite structure per each sensor), hit sequences can provide-

200..,......------------,

en

"0

c

§en 150
2

.g

E

i

=
is
Q)

100

60

.f:

40

<

7. Implications for AE Source Location
The above discussion demonstrates that, if acoustic
emission is to be applied for the nondestructive strength
evaluation of large fiber/polymer composite structures.
more accurate source location approaches must be developed. Two potential approaches seem possible at this time.
First. a wavefonn-based AE system could be used that could
provide consistent hit arrival times based upon using thesame fixed group velocity at each sensor. This approachhas been examined for simulated AE by Ziola and Gorman(1992). Second. a multi·level threshold approach may pr0vide a hardware-based approach. These approaches, as wellas others, need to be studied with wideband, small aperture
sensors on large composite structures.

8. Conclusions(1) Standard AE parameters such as peak amplitude, risetime. energy and duration used for characterization of
AE hits in graphite/epoxy composite plate or shell-likestructures experience large changes in the transition
from the near-field to the far-field. Also. the spectral
content of an AE signal changes significantly for nearfield versus far-field measurements.
(2) Even over rather short distances (e.g.• 60 mm) of pr0pagation, large changes in hit peak amplitude and energy occur. Thus, it does not make sense to characterize the significance of an event or the type of source
by using standard AE parameters or spectral content unless the effect of the propagation distance from thesource to the sensor is taken into account.

50
80

~

i=
c;;

some reasonable area locations of AE events. but errors will
also be present. Since high sensor densities are not typically feasible for large composite structures due to economic
constraints. other approaches need to be developed for accurate source location.

(3) Differences in the far-field AE waveform characteristics
arising from different composite AE source mechanisms require fundamental study with large composite
specimens.

20

0
20

30

40

50

60

70

FIXed Threshold (dB)

Fig. 15 Arrival time differences between AE hit anival
times for sensors #15 and #9 (spaced 410 nun apart) for
various fixed thresholds: (a) AE event shown in Fig. 4(peak amplitudes of 74 dB and 57 dB (484 mV and 73 mV
with 40 dB gain) at sensors #15 and #9, respectively); (b)AE event shown in Fig. 6 (peak amplitudes of 71 dB and 72
dB at sensors IUS and #9, respectively). (Reference 0 dB = 1~V out of the sensor).

(4) Large source location inaccuracies in a graphite/epoxy
plate or shell·like structure are primarily due to the useof fixed thresholds to determine hit arrival times. rather
than being due to the inherent nature of the AE signals.

References
CARP (1987), "Recommended Practice for Acoustic Emission Testing of Fiberglass Reinforced Plastic Resin (RP)
TankslVessels," The Composites Institute of the Society of
the Plastics Industry, Inc., New York.

K.S. Downs and M.A. Hamstad (1995a). "High Sensor
Density Acoustic Emission Monitoring of GraphitelEpoxy
Pressure Vessels," Proc. of Fifth International Symp. on
Acoustic Emission from Composite Materials (AECM-5),
Sundsvall, Sweden, The American Society for Nondestructive Testing, Columbus, OH (in press).
K.S. Downs and M.A. Hamstad (1995b). "Differences inGeneration and Detection of Acoustic Emission B~ on a
Large Number of AE Sensors on GraphitelEpoxy Pressure
Vessels." Proc. of Fifth International Symp. on Acoustic
Emissionfrom Composite Materials (AECM-5), Sundsvall,
Sweden, The American Society for Nondestructive Testing.
Columbus, OH (in press).
T.M. Ely, and E.v.K. Hill (1992), "Characterization of
Failure Mechanisms in GraphitelEpoxy Tensile Test Specimens using Acoustic Emission Data." Proc. AECM-4, The
American Society for Nondestructive Testing, Columbus.
OH. pp. 436-449.
M.A. Hamstad (1992), "An Examination of Acoustic Emission Evaluation Criteria for Aerospace Type Fiber/polymer
Composites:' Proc. AECM-4. The American Society for
Nondestructive Testing, Columbus, OR, pp. 436-449.
W.H. Prosser and M.R. Gorman (1992), "Propagation of
Flexural Mode AE Signals in GRIEP Composite Plates,"
Proc. AEcM-4. The American Society for NondestrUctive
Testing, Columbus. OH. pp. 418-427.
K.L. Reifsnider and J.E. Masters (1978), "Investigation ofCharacteristic Damage States in Composite Laminates", 78WAJAero 4. ASME Wmter Annual Meeting, San francisco, CA, Dec. 10-15.
R.L. Weaver and Y.R. Pao (1982), "Axisymmetric Elastic
Wave Excited by a Point Source in a Plate," 1. Applied
Mechanics, 49, Dec., 821-836.
S.M. Ziola and M.R. Gorman (1992), "Acoustic Emission
Source Location in Thin Plates using Cross-correlation."
Proc. AECM·4, The American Society for Nondestructive
Testing, Columbus. OR, pp. 411-417.

Historical Files
Compiled by T.F. Drouillard

AEWG MEETINGSMEETING LOCATIONDATE

MTG.CHAIR

Formative
1st
2nd
3rd
4th

Nov 2.1967
Feb 8-9. 1968
Aug 29-30. 1968
Feb 20-21, 1969
Oct 14-15. 1969
May 14-1S, 1970
Nov 12-13, 1970
May 20-21, 1971
Dec 7-9, 1971
Jun 14-16, 1972
Dec 6-8, 1972
Jut 18-20. 1973
Dec 5-7. 1973
Aug 19-21. 1974
Apr 28-30, 1975
Jan 20-23, 1976
Oct 18-20, 1976
Jun 14-16. 1977
Apr 17-20. 1978
Oec S- 7, 1978
5ep 10-13, 1979
Jun 29-Jul 2. 1980
Mar 9- 11, 1981
Dec 1-3, 1981
Sep 5-8, 1982
Jun 26-29. 1983
Apr 2-5, 1984
Feb 4-7, 1985
Oct 28-Nov 1,1985
Jun 23-26, 1986
May 12-14, 1987
Mar 21-24, 1988
Mar 20-23. 1989
Jan 16-19, 1990
Nov 12-15, 1990
Sep 15-18, 1991
Mar 17-19, 1993
Mar 14-17, 1994
May 1-4, 1995

J.C. Spannernone
D.L. Parry
Phillips Petroleum
R.W. Moss
Boeing Scientific Research Lab
C.W. Musser
Boeing Aerospace Division
T.F. Drouillard wI ASM Congress & ASNT Conf.
R.B. Engle
Lawrence Radiation Laboratory
T.T. Anderson Argonne National Laboratory
L.H. Glassman Georgia Institute ofTechnology
R.G. Liptai
wI ASTM Symposium on AE
T.F. Drouillard Dow Chemical & Univ. of Denver
E.Y. Robinson Jet Propulsion Lab & Endevco
P.H. Hulton
Battelle-Northwest Laboratories
W.F. Hartman Trodyne & Grumman Aerospace
D.O. Harris
DuneganJEndevco
W.O. Jolly
Southwest Research Institute
W.F. Hartman wI ASTM Committee E7 on NOT
R.L. Girouard
NASA-Langley Research Center
R.B. Engle
Lawrence Livermore Laboratory
lA. Simmons National Bureau of Standards
T.H. Feiertag
Los Alamos Scientific Laboratory
H.L. Dunegan wI 1st Inti. Conference on AE
W. Sachse
Cornell University
T.P. Drouillard Rockwell International Corp.
J.A. Baron
Ontario Hydro Research Division
W.F. Hartman Technology for Energy Corp.
SJ. Vahaviolos Physical Acoustics Corp.
A.T.Green
AE Technology Corp.
W.O. Jolly
Southwest Research Institute
A.T.GreenwI 2nd Ind. Conference on AE
SL. McBride
Royal Military College, Canada
O.M. Egle
University of Oklahoma
K.Ono
University of California. LA
W.Sachse
w/3rd World Conference on AE
O.A. Dornfeld University of California, Berkeley
H.L.M. dos Reis University of Illinois
S.J. Vahaviolos w/4th Inti. AE Conf. & ASNT
5.H. Carpenter University of Denver
A.T.Green
Acoustic Technology Group
W.H. Prosser
NASA-Langley Research Center

Sth

6th
7th
8th
9th
10th
11th
12th
13th
14th
15th
16th
17th
18th
19th
20th
21st
22nd
23rd
24th
25th
26th
27th
28th
29th
30th
31st
32nd
33rd
34th
35th
36th
37th
38th

Alcoa. Tennessee
Idaho Falls. Idaho
Seattle. WA
New Orleans. LA
Philadelphia, PA
Las Vegas. Nevada
Argonne. D1inois
Adanta, Georgia
Bal Harbour. FL
Denver. Colorado
Pasadena, CA
Richland. WA
New York City
Laguna Hills. CA
San Antonio, TX
Ft. Lauderda1e, FL
Williamsburg, VA
Livermore, CA
Gaithersburg. MD
Los Alamos, NM
Anaheim,CA
Ithaca, NY
BouJder,COToronto, Canada
Knoxville, TN
Princeton. NJ
Reno, Nevada
San Antonio, TX
Lake Tahoe. NV
Kingston, Ontario
Norman, Oklahoma
Los Angeles. CA
Charlotte, NC
Berkeley, CA
Urbana, Illinois
Boston, Mass
Denver, Colorado
Sacramento, CA
Hampton, VA

42

HOST ORGANIZATION

AWARDS of the ACOUSTIC EMISSION WORKING GROUP
GOLD MEDAL AWARD
Clement A. Tatro
Allen T. Green
Harold L. Dunegan
Adrian A. Pollock
Timothy J. Fowler
Prof. Morio Onoe
H. Reginald Hardy, Jr.
Steve H. Carpenter
Kanji Ono

24th meeting, Knoxville. Tennessee
25th meeting, Princeton, New Jersey
26th meeting, Reno, Nevada
27th meeting, San Anlonio, Texas
29th meeting, Kingslon, Ontario, Canada
8th Inti. AE Symposium, Tokyo, Japan
31 st meeting, Los Angeles, California
34th meeting, Urbana, llIinois
35th meeting, Boston, Massachusetts

September 7, 1982
June 29, 1983
April 4, 1984
February 6. 1985
June 25, 1986
October 22, 1986
March 22, 1988
November 14.1990
September 16. 1991

24th meeting. Knoxville. Tennessee
25th meeting. Princeton. New Jersey
26th meeting. Reno, Nevada
27th meeting, San Antonio. Texas
28th meeting. Lake Tahoe. Nevada
29lh meeting. Kingston, Ontario. Canada
31 st meeting. Los Angeles. California
35lh meeting. Boston. Massachusetts
11th Inti. AE Symposium. Fukuoka, Iapan
37th meeting, Sacramento. California
38th meeting. Hamplon. Virginia

September 7, 1982
Iune 29. 1983
April 4, 1984
February 6, 1985
October 29, 1985
Iune 25, 1986
March 22, 1988
September 16, 1991
October 28. 1992
March 16, 1994
May 3.1995

25th meeting. Princeton, New Iersey
27th meeting, San Antonio. Texas

Iune 29. 1983
February 6, 1985

34th meeting, Urbana, nlinois

November 14, 1990

38th meeting. Hampton. Virginia

May 3.1995

Formative meeting. Alcoa, Tennessee

Nov 2.1967

ACHIEVEMENT AWARD
Harold L. Dunegan
Julian R. Frederick
Nelson N. Hsu
H. Reginald Hardy, Jr.
Kanji Ono
Steve H. Carpenter
Dwight L Parry
Marvin A. Hamstad
Prof. Kuuo Yamaguchi
P. Richard BlackburnThomas M. Prodor, Jr.

PUBliCATION AWARD
Thomas F. Drouillard
Franklin R. Breckenridge
Martin GreenspanCarl E. Tschiegg
Ronnie K. Miller
Paul Mcintire
Clint R. Heiple
Steve H. Carpenter

HONORARY MEMBERJack C. Spanner, Sr.

SPECIAL RECOGNITION AWARD
Richard K. Steele

37th meeting, Sacramento. California

March 16. 1994

FELLOW AWARD
24th meeting. September 6. 1982
Clifford D. Bailey
Steve H. Carpenter
Thomas F. Drouillard
Harold L. Dunegan
Robert B. Engle
Allen T. Green
Philip H. Hutton
Kanji Ono
Clement A. Tatro

25th meeting. Iune 29, 1983
Alan G. Beattie
Albert E. Brown
Davis M. Bgle
Iulian R. Frederick
H. Reginald Hardy. Ir.
William F. Hartman
William D. lolly
Dwight L. Pany
Adrian A. Pollock

FELLQWAWARD <continued)
25th meeting, June 29, 1983
Jack C. Spanner, Sr.
26th meeting, April 4, 1984
Lloyd I. Graham
Marvin A. Hamstad
John W. McElroy
27th meeting, February 6, 1985
M. Nabil Bassim
Thomas H. Feiertag
Arthur E. Lord, Ir.
Sotirios J. Vahaviolos
28th meeting, October 29, 1985
John A Baron
Iohn M. Carlyle
29th meeting, Iune 25. 1986
Robert M. KoernerDavid W. Prine

30th meeting, May 13, 1987
Nelson N. Hsu
31st meeting, March 23,1988
D. Roben Hay
34th meeting, November 14. 1990
Clinton R. Heiple
Ronald A. Kline
Stuan L. McBridelames R. Mitchell
Wolfgang Sachse
Jerry W. Whittaker
37th meeting, March 16, 1994
Frank C. Beall
Henrique L.M. dos Reis
38th meeting, May 3, 1995
P. Richard BlackburnThomas M. Proctor, Jr.

Call for papers

1'95 SUBSCRIPTION RATE

22nd European Conference on Acoustic
Emission Testing, incorporating
EWGAE, May 29-31, 1996, Aberdeen,UK
Contributions are invited on all aspect of
acoustic emission theory. measurement and testing. The deadlines are as follows:
Submission of abstracts by: 6 November 1995.
Selection and notification by: 27 November
1995. Full papers must be available by: 26
February 1996. Announcement of final program:
26 February 1996. See p. 30 for more info.

The proceedings will be published. The priceof one copy is included in the conference fee. 1beattendance fee for the J..day meeting inclusive ofconference proceedings, lunches, social eventsand conference dinner is £235. Registration after
30 April 1996 will carry a 15% surcharge.
Aberdeen is an economically thriving mi
beautiful city of over quaner of a million people.
With all the attractions of a cosmopolitan city,
Aberdeen is identified as one of the UK's top
cities in tenns of quality of life. Surrounded by
the scenic splendour of the Grampian Highlands
with magnificent rivers, mountains, romantic
castles. beautiful gaJdens and the only Malt
Whisky Trail in the world, Aberdeen offers
visitors to the area a truly unique Scottish
experience.

Cor Volume 13

Base rate for one year (four issues, Mar. - Dec.) $ 96.00
Add Postage of U.S. - Book rate
$ 8.00All others - Book rate
$ 11.00
Western Europe/S. America - Air mail rate
S 25.00
All others • Air mail rate
$ 30.00
Add $5 without payment upon order. Payment must be in U.S.
dollars drawn on a U.S. bank. Bank transfer accepted to the
A.E. Group account (Account No. 080-03416470) at
Sumitomo Bank of California
San Fernando Valley Office15250 Ventura Blvd
Shennan Oaks. CA 91403-3262
Notify us of such a transfer as the bank cannot sometimes giveus the name of the payer. One volume of four issues per year.
Index included in the Oct.-Dec. issue. Back issues available at$50 per volume for Vols. 1·3, $90 per volume for Vols. 4.8,
$96 per volume for Vols. 9-12. US surface postages $8 pervolume. For Canada and overseas surface delivery. add $11 andfor air mail, di $30 per volume (will be adjusted for multivolume order).
AU orders should be sent to (or Fax 1-818-368-8309)
Acoustic Emission Group308 Westwood Blvd., Box 364
Los Angeles, CA '0024·1647
USA
For inquiry through Internet, use the following address:

ono@seas.ucla.edu
Editor-Publisher
Cover Design
Production

Kanji 000 Tel. (310) 825-5233
Robin Weisz (UCLA Publications)
Pace Publication Ans

Publication Date of This Issue: 31 July 1995.

44

12th International AE Symposium. Sapporo. Japan

A Waveform Investigation of the Acoustic Emission
Generated during the Deformation and Cracking of7075 Aluminum
Steve H. Carpenter and Michael R. Gorman
Abstract
The acoustic emission (AE) generated during the deformation of 7075 aluminum alloys has been the subject ofnumerous investigations. It is well known that the AE generated is strongly dependent on the prior thermal ammechanical treatment of the sample material. Possible sources of AE during deformation have been suggested as theavalanche motion of dislocations. fracture of brittle intermetallic particles and debonding of these particles from thealloy matrix. The goal of the present investigation was to determine if different sources of the AE could be identified
by characteristics of the waveforms produced. The AS was measured using non-resonant, flat. wide band transducers
with a new instrument. which measures and digitizes the entire AS waveform. An excellent correlation between AE
sources and measmed waveforms was established. Recently. it has been suggested that a significant portion of theAS generated during fatigue crack growth in the 7075 aluminum alloy is due to plastic deformation at the crack tip.
Measurements were carried out during fatigue crack growth and the waveforms were measured and characterized.
Analysis of the waveforms generated during fatigue crack growth showed no evidence of AE that could be attributed
to plastic deformation similar to that occurring at yield.

1. IDtrodudioD
The AE generated during the plastic deformation of aluminum alloys has been investigated in detail bynumerous investigators (Graham. 1976; Heiple et at. 1981; see also refs. in Drouillard. 1979 and Miller am
McIntyre. eds.• 1987). In particular. the AE generated during the deformation of 7075 aluminum alloys has been thesubject of numerous investigations (Graham. 1976; Carpenter and Higgins. 1977 Hamstad et al.. 1977; McBride etaI.. 1981). It has been clearly established that the AE generated is strongly dependent on the prior thermal ammechanical treatment of the test materials. The 7075 aluminum alloy is most commonly used in engineering
applications in what is known as the T65 I condition. The T6 designation indicates the heat treatment for maximum
strength and the -51 suffix indicates that the material was stretched approximately 3% after heat treatment to provide
flatness. The AS generated during tensile testing of a 7075-T65 I aluminum alloy sample is shown schematically in
Fig. l(a). The AS is characterized by a broad peak of AS occurring at 2-3% strain (well beyond yield), which
gradually reduces as the strain is increased. The AE generated during the deformation of a 7075-T6 aluminum sample.
i.e.• one that has not been stretched after heat treatment, is somewhat different as shown schematically in Fig. I(b).
Notice that in addition to the AS peak which occurs at 2-3% strain, there is an additional small peak of AS which
occurs at yield. If either the 7075-T6 or the 7075-T651 is solution treated and quenched before tensile testing. a
different AS result is obtained as shown schematically in Fig. 2. In this case, the AE peak at yield is enhanced am
the peale which occurs at 2-3% strain is absent. It has been established that the AS measured at yield is due to theavalanche motion of dislocations and that the AE producing the peak at 2-3% strain is due to the fracture anddebonding of large intermetallic inclusions/particles in the 7075 aluminum alloys (Carpenter and Higgins. 1977;
Hamstad et al.. 1977; McBride et aI., 1981). The AS, together with total wavefonns, has been measured andcharacterized during tests similar to those shown in Figs. 1 and 2. It will be shown that the measured waveforms canbe correlated very well with the different sources of AE.
Received October 20. 1994. S.H. Carpenter is affiliated with Physics Department. University of Denver. Denver. CO 80208(scarpenl@du.edu) and M.R. Gorman is wilh Digital Wave Corp.• Englewood. CO 80112. Based on a paper thai was given at
the 12th International Acoustic Emission Symposium. Sapporo. Japan and was included in the proceedings. Progress in
Acoustic Emission VII. JSNDI, Tokyo. Japan.

Journal of Ac:ollSric: Emission
Volume 13. Numbers 112

S1

07~SJ$S.OOIl3S01·S07

Copyright €>199SAcoustic: Emission Group

12th International AE Symposium, Sapporo, Japan
Applied stressI"'f--- Event rate or
rmsvoll8ge

Test time or strain
Test time or strain(a) T6S1(b) T6
Fig. 1 Schematic representation of the AE measured from the tensile deformation of a 7075 aluminum alloy.
Fatigue crack growth in 7075 aluminum alloys
was originally believed to be due to the fracture of MgSi inclusions by the advancing fatigue crack (McBrideand Maclachlan, 1983). This conclusion was based
primarily on the remarkable agreement between thenumber and area-size distribution of the inclusions in asection parallel to the fatigue crack plane and thenumber and amplitude distribution of the observed AE
signals. More recent measurements on 7050 aluminumaUoy (an aluminum alloy similar to 7075 with a much
lower inclusion content) found fewer AE events, butwith amplitudes larger than those observed in the 7075
aluminum alloy (McBride, unpublished research). These
Test time or strain
observations led McBride et a1. (1988) to propose thatthe source of AE during fatigue crack growth wasFig. 2 Schematic representation of the AE measured
from the tensile deformation of a solution treated am
intense plastic flow ahead of the growing crack. An
quenched 7075 alloy.
elegant investigation carried out in England (Bunle am
Scruby, J990) has suggested that the AE during fatigue
crack growth in 7075 aluminum alloys is due to the actual advancement of the fatigue crack, but work by Heiple etat (1992) has shown that the AE signal produced by deformation in the plastic zone ahead of the growing fatigue
crack is too small for the observed AE. The elastic energy released by the actual crack advance is consistent with thesize of the AE signals produced. Waveforms of the AE produced during fatigue crack growth have been measured andcompared with those measured during plastic deformation at yield. No waveforms characteristic of plastic deformation
were found during fatigue crack growth.

2. Experimental

AE measurements were carried out using a Fracture Wave Detector (model F4ooo, Digital Wave Corp.,
Englewood, CO). The Fracture Wave Detector allows for the digitization of the total AE waveform. The digitization
rate was 12.5 MHz with 1024 bytes per waveform using a threshold of 33 dB (in reference to 1 J1V = 0 dB). The
insaument is capable of capturing 65 waveforms per second on each of four channels. but this high capture rate was
not obtained in the present investigation. High fidelity, broadband transducers (Digital Wave Model B 1000) wereused to detect the AE. The transducers are specifically designed for broadband AE measurements over a frequency
range of 50 kHz to 3 MHz.
Tensile samples used during the deformation experiments had the following approximate measurements; gagelength 5.1 em, width 1.3 cm and thickness 0.6 em. All tests were carried out using an MTS-880 testing machine at52

12th Intemational AE Symposium, Sapporo, Japancrosshead speeds between 0.05 and 0.13 cmlmin. Two transducers were used, one at each end of the gage length toinsure that the measured AE originated from within the gage volume. Two types of fatigue crack growth experiments
were carried out. In one set of experiments samples similar to the tensile samples were used. For the other set ofexperiments, a larger sample, 30.5 cm gage length, 3.8 em wide and 0.3 cm thick, was used. In both cases a sharp
notch was used to initiate the fatigue crack. Loading was at a constant amplitude in tension-tension loading at a fre·quency of approximately I Hz. Two broadband transducers were attached at each end of the gage length. In a numberof tests an additional resonant transducer was attached to the test specimen very close to the sharp notch. The cntek
growth was observed with a high power video microscope capable of 2S J.UI1 resolution.
3. Results and Discnssion

In this section a number of the captured AE waveforms will be shown and discussed. However, only representative waveforms of the different AE sources will be shown. In general, large changes or differences from the waveforms shown were not observed. An attempt will be made to relate properties or characteristics of the measured waveforms to what would be expected from the proposed AE sources. The discussions will be given in terms of what
would be expected from plate wave theory as presented by Gorman (1991).
Figure 3 shows waveforms typical of the AE measured at yield, with waveforms from both transducers shown.
Waveforms at yield were captured from both the 7075·T6 and the solution treated and quenched samples. The waveforms were similar in nature, independent of the sample material. The time interval for all of the waveforms shownis 80 J1S. As can be seen the waveforms were typically of low amplitude and would often trigger on only one of thettansducers. It is believed that the source of these waveforms is the avalanche motion of dislocations. The observed
waveforms are consistent with that type of source, basically rapid slip, as shown by the fact that a large flexural
mode is present with little or no extensional mode.
Three different types of AE waveforms were observed in the AE peak which occurs at 2-3% strain. The three different types were observed during testing of both the 7075·T6 and the 7075·T6S1 sample materials. The three different types of waveforms have been attributed to:(I) non propagating sources such as noise,(2) fracture of intermetallic panicles and(3) debonding of the intermetallic particles from the matrix.
Figure 4 shows waveforms. which were attributed to noise or non propagating sources of AE. An examination ofFig. 4 shows that even though the transducers were separated several em, both the initiation and time dependent character of both b'anSducers is essentially identical. In this case the source must be directly at the center of transducer
array or more likely the AE is due to non propagation noise sources such as electromagnetic radiation. Figure 5
shows examples of the most common of the waveforms observed during the AE peak at 2-3% strain. In general, theamplitude was higher than the waveforms measured at yield and the propagation characteristics are clearly evident.
The AE source producing this type of waveform is believed to be the fracture of intermetallic particles within thematrix. The nature of the waveforms is consistent with that observed for crack propagation and discussed in detailelsewhere (Smith. 1990). The third type of waveform observed during the AE peak at 2-3% strain is shown in Fig.
6. The waveform is very similar in nature to those measured at yield (cf. Fig. 3). The source of this type of waveform is believed to be due to defonnation around or debonding of the particles from the matrix. Analysis of a numberof different tests provided the following statistics for the AE peak at 2-3% slrain, 66 - 75% of the waveforms captured could be categorized as waveforms from the cracking of intermetallic particles. 11- 18% of the waveforms captured were categorized as being similar to the waveforms observed at yield and are believed to be due to debonding of
the intermetallic particles from the matrix, and 10 - 13% of the captUred waveforms were associated with noise orother non propagating sources of AE.
The AE during fatigue crack growth was also monitored for the two sizes of samples, as mentioned earlier. In
both cases two types of waveforms were observed, one type that could be related to crack growth or extension and theothers could be shown to be some type of extraneous noise. Figure 7 shows waveforms due to extraneous noise captured during the fatigue testing of the smaller samples (S.O em gage length). With the two sensor array it was easy toattribute the waveforms shown in Fig. 7 to noise since the waveform shape and propagation time indicated that thesource must be outside of the transducer array. Figure 8 shows waveforms attributed to the crack extension of thefatigue crack. Notice the similarity of these waveforms with those shown in Fig. 5 due to cracking of the53

12th Intemational AE Symposium. Sapporo. Japan

Fig. 5 Typical wavefonns from the AE measured at 23% strain, atbibuted to fracture of intennetallic particles. The wavefonn length: 80 IJ.S.

Fig. 3 Typical waveforms from the AE measured atyield during defonnation of 7075 Al alloys. The lengthof the waveforms: 80 JiS.

--.4'10"
V

....

-

-

Jll.J M.
V'rlff\'"Fig. 6 Typical wavefonns from the AE measured at 23% strain, attributed to debonding of intermetallic particles. The waveform length: 80 IJ.S.

Fig. 4 Typical wavefonns from the AE at 2-3% strain
attributed to noise. The wavefonn length: 80 JiS.

intermetalJic particles. The in-plane source motion produces a larger ampJitude extensional wave relative to the flexural wave, than does an out-of-plane motion. This is why inclusion fracture and crack advance waveforms look sosimilar. Figure 9 shows waveforms attributed to crack extension during testing of the larger samples (30 em gagelength). Included in these waveforms is a wavefonn from a resonant (Dunegan 59204, ISO kHz) transducer for comparison. In this array the resonant transducer is located very near the fatigue crack. Notice the distinct separation of
the extensional and flexural modes due to the larger nature of the sample.
During the testing of the larger samples a significant amount of AE due to grip noise was encountered. Figure
10 shows the waveform captured due to grip noise. A disturbing feature to notice is that using the resonant transducer no distinguishable difference exists between wavefonns from crack extension and those from grip noise. In allof the fatigue crack measurements, on both types of samples, the majority of the waveforms captured had similar
characteristics as those attributed to fracture of intermetallic particles in the tension testing. No waveforms were captured which had the characteristics previously identified with plastic deformation of the matrix or from debonding

54

12th International AE Symposium, sapporo, Japan(a)Fig. 7 Typical waveforms from the AE measured during fatigue. small sample. AtUibuted to extraneous
noise. The wavefonn length: 80 J.lS.

(b)Fig. 8 Typical waveforms from the AE measured during fatigue. small sample. AtUibuted to crack extension. The wavefonn length: 80 J1S.
of the intennetallic panicles from the matrix. A surprising result during the fatigue testing was the large
amount of AE. which could be attributed to noise andin particular to grip noise. In some experiments, over
50% of the measured AE could be atUibuted to grip
noise even though the experimental conditions would
suggest that there was no noise presenL(c)

4. Conclusions
The fo))owing conclusions were reached as a resultof this investigation:
1. The AE measured at yield during the tensile testingof 7075 aluminum alloys contained only one basic

Fig. 9 (a-c) Typical waveforms from the AE measured
during fatigue of a large sample. Attributed to crack
extension. The waveform length: 80 J1S.

55

12th International AE Symposium, sapporo. Japan

wavefonn; see Fig. 3. The AE has been attributed
to avalanche motion of dislocations occurring at
the elastic yielding of the matrix.
2. The AE measured at 2-3% strain during the tensile
testing of 7075 aluminum alloys was characterized
by three basic wavefonns. Approximately 10-13 %of the wavefonns captured were similar to the one
shown in Fig. 4. The source of this type of wavefonn has been attributed to noise or other non pr0pagating sources. The identification of the sourceof the waveforms similar to those shown in Fig. 4
was based on the propagation time relationships ofthe two wavefonns. The majority of the AE, 6675% of the waveforms, was similar to the ones
shown in Fig. 5. The AE source of this waveformis believed to be the fracture of intermetatlic particles in the matrix due to the striking similarities ofFig. 10 Typical wavefonns from the AE measured
these waveforms to waveforms known to be fromduring fatigue of a large sample. Attributed to grip
crack advance. The third type of waveform isnoise. The waveform length: 80 J1S.
shown in Fig. 6, 11-18% of the total were of thistype which is believed to be due to debonding of
the intennetallic particles from the matrix. Notice the similarity with the waveforms shown in Fig. 3.
3. Two types of wavefonns were observed during the fatigue cracking of the 7075-T651 aluminum alloys. The
majority of the wavefonns were believed due to crack extension and are shown for the two different size samples
in Figs. 8 and 9. The waveforms are consistent with wavefonns known to be from crack extension (Smith,1990) and have similar characteristics with those attributed to cracking of the intermetallic particles. During fatigue crack growth no waveforms were captured which could be associated with plastic deformation. In somecases large amounts of AE which could be shown to be due to grip noise was observed. The grip noise was o~served even though the experimental conditions would not have suggested its presence. The waveforms from theresonant sensor showed no differentiation of the AE from the grip noise with that from actual crack extension.

References
OJ. Buttle and C.B. Scruby (1990), J. Acoust. Emiss., 9, 234-254.
S.H. Carpenter and F.P. Higgins (1977), Metal!. Trans. A. SA, 1629-1632.
T.F. Drouillard (1979), AcoUJtic Emission, A Bibliography with Abstracts, 1st ed., IFIIPlenum, New York, NY.
M.R. Gorman (1991), I. Acoost. Soc. Amer., 90,358-364.
LJ. Graham (1976), Proceedings of the ARPAlAFML Review of Quantitative NDE, AFML-TR75-212, Science
Center, Rockwell International, Thousand Oaks, CA, pp. 631-642.
M.A. Hamstad, R. Bianchetti and A.K. Mukherjee (1977), Eng. Fraet. Mech., 9, 663-674.
C.R. Heiple, S.H. Carpenter and M.J. Carr (1981), Metal Science, 15,587-598.
C.R. Heiple, S.H. Carpenter and D.L. Armentrout (1992), I. Acoust. Emiss., 10, 103-106.
S.L. McBride, J.W. Maclachlan and B.P. Paradis (1981), I. Nondestr. Eva!., 2, 35-41.
S.L. McBride and J.W. Maclachlan (1983), I. Acoost. Emiss., 4, 179-185.

56

12th International AE Symposium, Sapporo, Japan

S.L. McBride, P. Bowman and K.L. McRae (1988), Progress in Acoustic Emission IV, eds. K. Yamaguchi et al.,The Japanese Society for Nondestructive Inspection, Tokyo, Japan, pp. 528-535.
R.K. Miller and P. McIntyre, eds. (1987), Nondestructive Testing Handbook, 2nd. ed., Volume 5, Acoustic Emission Testing, American Society for Nondestructive Testing, Columbus, OH.
W.D. Smith (1990), "Acoustic Emission from Spectrum Fatigue Cracks in 7075 Aluminum", M.S. Thesis, Naval
Postgraduate School, Monterey, CA.

COVER PHOTOGRAPH
The photograph on the cover of this issue was taken during spectrum fatigue testing of a stiffened wing skin panel atNonhrup. A repon on the test was given at the 37th AEWG meeting by S. Ziola, who used the same type of AE
instrument as in the above paper.

12th International AE Symposium. Sapporo. Japan

Acoustic Emission and Damage Evolution in an SiC
Fiber Reinforced Ti Alloy Composite
K. Takashima, H. Tonda and P. Bowen
Abstract
Damage evolution in an SiC fiber reinforced Ti alloy composite (SCS-6ITi-6AI-4V) has been assessed by acoustic emission (AE), stiffness loss and internal friction (mechanical damping). Damage in the composite was introduced by four point bending through both a series of step-wise monotonic loading and unloading sequences, and cyclic loading. AE signals were monitored during the tests, and Young's modulus and internal friction were measured
by a flexural resonant method. In both stepwise loading and cyclic loading, the Young's modulus decreased by only
I % before failure of the specimen. However, the internal friction began to increase gradually after loading, and increased rapidly prior to failure in both types of tests. Cumulative AE energy increased with increasing internal friction in both types of tests. These results suggest that the evolution of damage in such composites can be assessed by
a combination of AE monitoring and internal friction measurements.

1. Introduction
Metal matrix composites are considered to be favorable candidate materials for aerospace structures or engine
components because of their high specific strength and high temperature strength. In particular, n alloys reinforced
with continuous SiC fiber are some of the most promising materials offering an excellent combination of high temperature strength, stiffness and toughness (Wadswonh and Frees, 1989),. For practical application of these composites, there is a need to develop non-destructive inspection techniques for the detennination of component quality after
fabrication, and for the assessment of damage throughout service. Damage process in composites involves various
mierofracture modes, such as fiber breakage, debonding between fiber and matrix, fiber sliding and pull out, and matrix cracking (Jeng et al., 1992). Since these fracture modes interact with each other, it is difficult to assess the damage progression and the amount of the damage in composites.
The acoustic emission (AE) technique is one of the most useful methods for assessing damage in composites.
Since AE signals contain information on source phenomena, the AE technique has potential for discriminating eachmicrofracture event in composites by suitable AE wave analyses. In addition, damage may cause both stiffness loss
and an increase of internal friction (mechanical damping) of composites. This suggests that both stiffness loss mIinternal friction may also be methods of assessment of damage in composites. However, most studies of AE, stiffness loss and internal friction measurements during damage evolution in composites have been carried out on fiber
reinforced plastics (Jeng et aI., 1988; Sanders et aI., 1992) and ceramic matrix composites (Tsuda et al., 1992; Habib
et aI" 1993). There are few studies to date which have been applied to Ti alloy based composites (Takashima et aI.,
1993; Bakuckas, Jr. et al., 1994). In this study, damage introduced by step-wise loading and fatigue tests in an SiC
fiber reinforced n alloy composite (SCS-6ITi-6AI-4V) has been assessed by acoustic emission (AE), stiffness loss
and internal friction (mechanical damping).

2. Experimental Procedure
2.1 Materials
Received October 20, 1994. K. Takashima and H. Tonda are affiliated with Department of Materials Science. Kumamoto
University. 2-39-1, Kurokami, Kumamoto 860, Japan and P. Bowen is with School of Metallurgy and MaterialsJIRC in
Materials for High Performance Applications, Edgbaston. Binningham BIS 211'. UK. (takashik@gpo.kumamoto-u.ac.jp).
Based on a paper that was given at the 12th International Acoustic Emission Symposium, Sapporo, Japan and was includedin the proceedings, Progress in Acoustic Emission VII, JSNDI, Tokyo, Japan.

Journal or Acoustic Emission

Volume 13. NurnbeJs 1/2

sa073().OO5QI95/SS.00I13S08-S13

Copyright 4) I99SAcoustk Emission Group

12th International AE Symposium, Sapporo, JapanThe material used in this study was a Ti-6AI-4V alloy unidirectionally reinfon:ed with continuous SCS-6(SiC) fibers (of 140 Ilm in diameter) fabricated by afoil-fiber-foil consolidation technique, and available
commercially. Specimens with dimensions of 75 mm
in length, 4 mm in width, 2 mm in thickness were cut
from 8-ply composites panels by electrical dischargemachining. The fiber orientation to the longitudinal direction was 0°. The fiber volume fraction in these composites was approximately 0.35. All specimens were
tested in as-fabricated condition, and no heat treatment
was performed prior to the test

Load Amp

2.2 Mechanical Testing and AE Measurement
Figure I shows an experimental setup and block
Fig. I Block diagram of measuring system.
diagram of AE measurement system. Damage growth in
the composite was introduced by four point bending through a series of step-wise loading and unloading sequences,and cyclic loading under constant load range. All tests were carried out using a servo-hydraulic testing machine. In
the stepwise loading, a sequence load was applied to the specimen every 0.5 leN up to failure. The loading rate was
set to 10 Nts. The cyclic loading test was conducted at a frequency of I Hz and the ratio of the minimum to maximum stress applied over the fatigue cycle, R = 0.1. The maximum load employed was 1.5 leN and this corresponds
to a maximum surface stress of approximately 1.4 GPa under the conditions of bending used in this present study.
This is approximately SO% of the static failure (flexural) strength observed in the step-wise loading test. In the tests,
two AE sensors were attached to the both ends of the specimen using silicone grease. The AE sensors used wereM53 (Fuji Ceramics Co.), and their resonance frequency is approximately 300 kHz. AE signals detected during tests
were amplified by a pre-amplifier and analyzed by an NF 9502 AE measurement system. The gain of the preamplifier was 40 dB. The threshold level was 100 IlV at the output of the sensor. In this study, AE events generated
only within the central loading span (constant bending moment region) were measured using spatial filtering.
Young's modulus and internal friction were measured by a free-free beam method. Young's modulus was determined from a fundamental flexural resonant frequency, and internal friction was measured by a resonance peak-width
method. Table I shows elastic moduli and internal friction values of the composite in the as-received condition
measured by this method.
Table I Elastic moduli and the internal friction values of the SCS-6Iri-6AI-4V.

194.5

140.7

79.1

52.9

0.23

0.17

0.33

2.25

5.07

3. Results aud Discussiou
3.1 AE Characteristics and Damage during Step-Wise Loading
Figure 2 shows the relation between load, cumulative AE events, event amplitude and time. AE events are generated at 0.2 leN of the first loading, but the number of events is small and their event amplitude is relatively low.
After the second loading, AE events start to increase when the load level exceeds the previous maximum load, amthe "Kaiser effect" is observed clearly. AE events during unloading are also detected. Although the event amplitude
during unloading is small, the number of events increase with an increase of load. The specimen failed at 2.8 leN
during the 6th application of load. Final failure occurred at the center of the specimen and corresponds to a surface
stress of 2630 MPa AE events increase abruptly prior to the failure of the specimen. Amplitude distributions of AE
events during loading are shown in Fig. 2. AE event amplitude values are shown with reference to 0.1 flV at theoutput of the sensor. No high amplitude events are observed at loads of up to 0.5 leN. Peaks at approximate 80 dB (lSB12th Intemational AE Symposium, Sapporo, Japanm V) are found at loads of up to ] kN, but the height of this peak decreases rapidly above 1.5 leN loads. High amplitude events start to be generated at loads above 1 kN, and distinct peaks at ]]0 dB (31.6 mY) are observed clearly.
This change in the amplitude distribution suggests that the dominant damage processes in the composite change progressively. In our previous investigation on AE characterization of a SCS-6162I S Ti alloy during fracture and fatigue(Takashima el aI., 199 ), high amplitude events were confinned to correspond to fiber fracture by direct optical observation, and low amplitude events were associated with fiber-matrix debonding by waveform analysis. Figure 4
shows an optical micrograph of the specimen near fracture surface. Fiber fracture and fiber-matrix debonding are 0bserved, and this indicates that these kinds of damage were produced during the test. Therefore, high amplitude events(over 100 dB) are considered to correspond to fiber fracture, and low amplitude events (60-80 dB) are considered tocorrespond to fiber debonding and/or fracture of reaction lone between fiber and matrix.

3

~~

~.
I

..

2500

..

•. ..-

120

2000

100

..

I·

~

-

I.

.

1500~

~

Z

~

:I
0

'U

()

! 1

1000)

~

500
0
500

1000
Tlme(s)

1500

2000

Fig. 2 Load-time curve with cumulative AE event counts and amplitude during step-wise loading.

lOQ

I

I
I

Fig. 3 Changes of amplitude distribution during step-wise loading.
Figure 5 shows the relation between Young's modulus. internal friction and the load. Young's modulus and, internal friction values are normalized by their measured values for the undamaged condition. Young's modulus ~creases by only t % of its initial value at loads of up to 2.5 leN which corresponds to 90% of the failure load (2.8810

12th International AE Symposium, Sapporo. Japan

2.4
1.00

--0

0.98

.. 0.96

~

:1

~E, I

-0-

-----A-- .. ·

.

..
.
.
.
..

0/00

A

./1••••••• 4·.4·······..

0.92 "-..' ..

: --

I

0.90
0.0

200J.lm

Fig. 4 Optical micrograph of specimen surface after
failure.

,b••••••

'
I

I

0.5

1.0

I

1.5
Load (kN)- 2.0- 1.8 a- 1.6 a.

0.94 -

22

I

I

2.0

2.5

- 1.4
- 12
- 1.0
3.0

Fig. 5 Relation between nonnalized Young's modulus
nonnalized internal friction and load during step-wiseloading.

-c

1 5 0 0 . . - - - - - - - - - - - - - - - . . . , 3.0E+09 _

;:)

---0-

Counts.... ·A.... ·Energy

.;

.I:.

.
....
...

:a

...

2.0E+09 $

~

,;

CIJ

c

au

1.0E+09i'S
E•••••••Ji

:::I

.'

U

O.OE+OO

0.0

0.5

1.0

1.5
2.0
Load (kN)

2.5

3.0

Fig. 6 Relation between cumulative event counts. cumulative AE energy and load during step-wise loading.
kN). However. the internal friction value starts to increase just after the first step-wise loading and increases by approximately 50% compared to that of its initial value. at 90% of the failure load. The metallographic observation in
Fig. 4 shows damage in the composite is due to fiber fracture and fiber-matrix debonding. but no transverse cracks inthe matrix are observed. This may be one reason that the stiffness loss is not remarkable in this composite. Amplitude distributions in Fig. 3 indicate that damage starts during the first step-wise loading. Therefore. the increase ininternal friction corresponds to progressive damage in the composite. Figure 6 shows the relation between cumulative AE event counts. cumulative AE energy and applied load. In this study. the AE energy of the event was defined
as a square of the event peak amplitude. AE event counts increase constantly, whereas cumulative AE energy starts
to increase above loads of I kN and increases rapidly above loads of 2 kN. and appears to show a good correlation
with the increase of internal friction. This result suggests that cumulative AE energy may be correlated to damage inthe composite. and thus may give a good indication of the severity of composite damage.
Figure 7 shows the relation between cumulative AE event counts. event amplitude and the number of cycles during cyclic loading. Fatigue fracture occurred after approximately 15.000 cycles. AE events are generated during thefirst loading cycle and increased gradually with increasing number of cycles. Sudden increases of AE events are foundjust before final failure, and high amplitude events are associated with it. The AE amplitude is distributed from 60 dB
to 90 dB for up to 10.000 cycles. This suggests that damage during this region corresponds to fiber-matrix debonding
and does not involve fiber fracture. Optical microscopy observation of the specimen after failure show s few fractured
fibers. and this supports the above interpretation of AE behavior.

811

12th International AE Symposium, Sapporo, Japan

SOO , . . . . - - - - - - - - - - - - - - - - - - - - . 120

400

SC

G!

>
w

-1:..

Events110

Amplitude

100 _
ID

:!!.

300

9OG!

...

0

• I

.•..

E

..

:::J

I' •

Z

i

80 Q.
E

.,•,
I

I.!."

•

WI
•\z::rI

~

t.

..
•

•

:.~

10

70

. .. • om•..... ," . ':....:.'

•

•

1

oC

••:I

.
... . .
I

\

100

60

~

1000

50

10000

Number of Cycles

Fig. 7 Cumulative AE event counts and amplitude of event versus number of cycles during cyclic loading.

......- - - - - - - - - - - - - - - - - - . 1 . 5\\t'"'~-o---oO--_4o.__-...e>-o-o-o

1.00

1.4
o

0.98

-----c---_.

ElEo
0/00

A

:

··
··

~ 0.96·•••• 4--------6-6- -d

0.94••••••• .6••••.. \.,\:.,

0.92

1.3
1.2

0

o

a

1.1

4'

1.0
1

10

100

1000

10000

Number of Cycles

Fig. 8 Relation between nonnalized Young's modulus. nonnalizcd internal friction and number of cycles.

8.0E+05

250
200

S

c

&
U

=C

--0-

Counts:)-----6----·

Energy6.0E+05 :is

.oJ

$

.

>CI

150

-

4.0E+05 cCD
w

c 100
>
w

!

III

III
2.0E+05 "5

50

E

:s

U

O.OE+OO
0

1

10

100

1000

10000

Number of Cycles

Fig. 9 Relation between cumulative event counts. cumulative AE energy and number of cycles

812

12th International AE Symposium, sapporo, Japan

3.2 AE Characteristics and Damage during Cyclic Loading
Figure 8 shows changes in Young's modulus and internal friction during fatigue. The reduction of Young's
modulus after 10,000 cycles is only I %. Internal friction begins to increase from the first loading cycle, and continues to increase up to 100 cycles. Although AE events are observed continuously, internal friction does not increase
from 100 cycles to 5000 cycles. The internal friction again increases suddenly between 5000 cycles and 10,000 cycles. This suggests that damage evolves rapidly during this period. However, cumulative AE energy stans to increase
after 1000 cycles, as shown in Fig. 9. This perhaps indicates that cumulative AE energy can be used to give the bestindication of progressive damage in these composites.

4. Conclusions
Damage evolution in a SCS-6!fi-6AI-4V was assessed by acoustic emission (AE), stiffness loss and internal
friction. Progressive damage in the composite was introduced by four point bending through both a series of stepwise monotonic loading and unloading sequences, and cyclic loading. In both types of tests. the Young's modulus
decreased by only I % until just before the failure of the specimen. However, the internal friction began to increase
gradually after loading in both types of tests, and increased rapidly prior to failure. Cumulative AE energy increased
with increasing internal friction in both types of tests. A combination of AE monitoring and internal friction measurement would appear to offer an effective assessment method for damage evolution in such composites.

Acknowledgment
This work was partly supponed by the Grant-in-Aid for Scientific Research on International Joint Research Program.
from the Ministry of Education, Science and Culture, Japan.
References
J.G. Bakuckas, Jr., W.H. Prosser and W.S. Johnson (1994), "Monitoring Damage Growth in Titanium Matrix
Composites Using Acoustic Emission", J. Compo Mal. 28, 305-328.
F.A. Habib, R.AJ. Taylor, R.G. Cooke and B. Harris (1993), "Fatigue Damage in Sic/CAS Composites", Composites,24, 157-165.
J.S. Jeng, K. Ono and J.M. Yang (1988), "Fracture Mechanism Studies of Carbon Fiber Reinforced Thermoplastic
Composites by Acoustic Emission", Progress in Acoustic Emission IV, Japan Soc. NDI, Tokyo, pp. 757-764.
S.M. Jeng, P. Alassoeur and J.-M. Yang (1992). "Fracture Mechanisms of Fiber-Reinforced Titanium Alloy Matrix
Composites", Mat. Sci. Engr.• A154, 11-19.
D.R. Sanders, V.I. Kim and N. Stubbs (1992), "Nondestructive Evaluation of Damage in Composite Structures Using Modal Parameters". Experimental Mechanics, 32, 240-251.
K. Takashima. K.M. Fox and P. Bowen (1993), "Acoustic Emission Characteristics During Fracture And Fatigue Of
Continuous Fiber Reinforced Titanium Alloy Composites", Proc. 3rd Japan. lot SAMPE, 2365-2370.

H. Tsuda. M. Enoki and T. Kishi (1992), "Interfacial Mechanical Propenies of Fiber-Reinforced Ceramic Composites". J. Ceramic Soc. Japan, 100, 530-535.
J. Wadsworth and F.H. Frocs (1989), "Developments in Metallic Materials for Aerospace Applications", J. Metals,
41(5), 12-19.

513

12th Intemational AE Symposium. Sapporo. Japan

Cracking Process Evaluation in Reinforced Concrete
by Moment Tensor Analysis of Acoustic Emission
Shigenori Yuyama, Takahisa Okamoto, Mitsuhiro Shigeishi and
Masayasu Ohtsu
Abstract

FraCbJIe tests were conducted on two types of reinforced concrete specimens WIder cyclic loading. Cracking
process is quantitatively evaluated and visualized by applying a moment tensor analysis to the AE waveforms
detected during the fracnue. First. bending tests were perfonned on reinforced concrete beams. It is found that bothtensile and shear cracks are generated around the reinforcement in the early stages. However. the ratio of shear cracks
increases as the cracking process progresses. Subsequently, shear cracks are initiated near the interface between thereinforcement and concrete even during unloading. Secondly, bond strength tests were made and showed that tensile
cracks are produced near the reinforcement in the early stages. They spread to wider areas in later stages. An intense
AE cluster due to shear cracks is observed along the interface between the reinforcement and concrete. These results
demonstrate the usefulness of the analysis for quantitative evaluation and visualization of the cracking process inreinforced concrete. The relationship between the opening width of surface cracks and the Kaiser effect is discussed. It
is shown that a breakdown of the Kaiser effect and high AE activities during unloading can be effective indices toestimate the level of deterioration in concrete stnJetures.
1. Introduction
In the area ofcivil engineering, the development of techniques to evaluate the degradation of concrete structuresin long-term service is one of the most important issues for an effective maintenance program. Since acoustic
emission (AE) is very sensitive for the initiation and growth of cracks in concrete. it has been widely used in both
concrete specimens (Okamoto et aI., 1991) and structures (Yuyama et aI., 1994).

There are two manners to analyze AE data acquired by two different types of conventional AE instrumentation.
Fmt one. which has been widely and more frequently applied. is parameter analysis. It analyzes relative AE activities
based on the measurement of such parameters as hit. count. energy, amplitude and so forth. Second one, which has
progressed greatly for the last ten years, is quantitative wavefonn analysis such as a source characterization (Kim am
Sachse. 1984; Enoki et aI., 1986), and a moment tensor analysis (Ohtsu, 1991). This deals with the quantitative
information on AE sources by applying theoretical treatment to the waveforms recorded by a mUlti-channel transient
recorder.
This paper descn'bes the results of the moment tensor analysis performed on two different types of reinforced
concrete specimens under cyclic loading. The results demonstrate the usefulness of the analysis for quantitativeevaluation and visualization of the crack locations, types and orientations. The relationship between the opening
width of surface cracks and the Kaiser effect is discussed. characterizing the general AE behavior during the fracture of
reinforced concrete. It is indicated that the Kaiser effect breaks down when shear ci'acks start to play the primary rolewith the crack width exceeding 0.12 mm. The breakdown of the Kaiser effect and high AE activities during unloading
are shown to be very effective indices to estimate the level of deterioration in concrete structures.
Received 20 October 1994. S. Yuyama is affiliated with Nippon Physical Acoustics Ltd.. 8F. Okamoto LK Bldg.• 2-17-10
Higashi, Shibuya-ku. Tokyo. ISO Japan. T. Okamoto is with Central Research Laboratory. Nihon Cement Co.• Ltd.• 1-2-23
Kiyosumi. Koto-ku. Tokyo 13S. Japan. M. Shigeishi is with Cooperative Research Center Kumamoto University. 2081-7
Tabaru. Mashiki-cho. Kumamoto. 861-22. Japan and M. Ohtsu is with Department of Civil and Environmental Engineering. Faculty of Engineering. Kumamoto University. 2-39-1, Kurokami. Kumamoto. 860. Japan (ohtsu@gpo.kumamotou.ac.jp). Based on a paper that was given at the 12th International Acoustic Emission Symposium. Sapporo. Japan and wasincluded in the proceedings. Progress in Acoustic Emission VII. JSNDI. Tokyo. Japan.

Journal of Acoustit Emission
Volume 13. Numbers 1/2814

0'730-00S()I95/SS.00I13S14-S20
Copyright el99SAcoustic Emission Group

12th International AE Symposium, Sapporo, Japan

2. Experiment

2. J Specimen and AE sensor Location Cyclic Bending Test
Shown in Fig. I is the configuration of a specimen used for the cyclic bending test. A single reinforcing bar of
19 mm in diameter with lateral lugs is encased off center in the rectangular concrete beam. Compressive and tensile
strengths of the concrete are 36.2 MPa and 3.5 MPa, respectively. The specimen was subjected to repeated four-point
bending load by a strain·control type machine. The maximum load of each loading cycle was increased gradually inorder to investigate the relationship between cracking process and AE behavior. Since a single tensile crack was
expected to be initiated in the center part of the tensile zone in the specimen, a displacement transducer was anachedon the bottom side of the specimen to measure opening width of the surface crack. Six AE sensors were placed on
the specimen surface. Figure 2 shows AE sensor locations on the specimen.

2.2 Bond Strength Test
Specimen configuration of the bond strength test ispresented in Fig. 3. A single defonned bar of 13 mm indiameter is encased in the center of the reccangularconcrete beam. Compressive strength of the concrete
was 28.0 MPa at the time of the test. The specimen
was subjected to tensile loading·unloading two times.
AE sensor locations are given in Fig. 4.
Fig. I Reinforced concrete specimen in bending test.

CH. NO.
1

X
0

3

Z

V

2

200

12

~

0

12

4

J

5

201
51

15
1c;
7

6

15

150

SO

Fig. 2 AE sensor locations for the bending test.

.. . ..

0··

"

0·.0·

o •

'1"

••

r<')

. T-

. '. . .'

,0.

'. 0

O'

0

• 0

••

0"0 ..•.. 0"'0_ .. 0 . , . 0 . 0 ]• ~·.a:.c~~~Dj:E.OR!::1~-.s~B..!..:':....~-=:.:~ I-------------~- .... --~0;"0' .',0 DIA'METER"3mm o

.'. 0

••• 0

•

•

o.

0

I.

0

•

0

•• ~.,.~:• • ·00
0.-•• 0 . •400.1Fig. 3. Reinforced concrete specimen in bond strength test.

2,3 AE Instrumentation
The same AE instrumentation as the one previously reponed (Yuyama et at.. 1995) was employed all throughthe tests. A six channel PAC LOCAN·AT system was used for the measurement of AE parameters. A six channel
PAC TRA-2.S system was employed for waveform recording. An AE signal detected by a PAC R·lS (ISO kHz
resonant) sensor that crossed the threshold (60 dB) in a predetennined channel of the LOCAN-AT triggered all TRA
cards to record a waveform set. Each waveform was digitized into 2K samples at a sampling rate of 2 MHz.

S15

12th International AE Symposium, sapporo, Japan

I, Sensor LOCe1tion unmI
CH
1
2
3
4
5

6

X
100
21
BI

81
3

Y
50

a
0

50
100
100

Z
30
?O
180
170
~o

180

Fig. 4 AE sensor locations for the bond strength test.

2.4 Moment Tensor Analysis
To classify crack type and to detennine crack orientation, a simplified moment tensor analysis based on acomputer program SiGMA (Ohtsu. 1991), was applied to AE waveforms recorded during the tests. Since AE sensors
were placed on the surface of the specimen, a program SiGMA developed for a half-space was employed for the
analysis. Shear component ratio (X in %), source location and crack orientation for each event were obtained fromeigenvalue analysis of a moment tensor. From the value of X, each crack can be classified into either tensile or shear
type. A pure tensile crack implies that the discontinuity vector is parallel to the nonnal vector, in which case X
becomes 0%. In contrast, a pure shear crack corresponds to the case where X = 100%. Thus, all events can beclassified into tensile cracks (X < 40%), medium cracks (40% < X < 60%), or shear cracks (60% < X).

3. Results
3.1 Cyclic Bending Test
Shown in Fig. 5 is the test loading history. The specimen was subjected to cyclic loading-unloading five times.
The maximum load was 49 leN in the 1st and the 2nd loading. It was gradually increased from the 3rd to the 5th
cycle.

2"6-r----------------.
1$147
IV

Z

v

o~98­_<
0/.9~

O-~_r--,.."_r_....:.r___,_;;.....,r___T_~~~__,I

o

500

1000
TIME (S)

1500

2000

2500

Fig. 5 Loading history in the bending test.

816

Figure 6 indicates the relationship between the
opening width of the tensile crack observed on thespecimen surface and the applied load. It is seen that thecrack width exceeds 0.12 mm during the 2nd loading.
Figure 7 presents the relationship between the numberof AE hits and the applied load. AE signals are detected
at a lower load than the maximum prior load (49 kN)
during the 2nd loading; i.e. the Kaiser effect starts tobreak down when the crack width exceeds 0.12 mm
during the 2nd loading.
Results of the moment tensor analysis are given in
Table I and Fig. 8. Number of tensile cracks (X <40%), medium cracks (40% < X < 60%) and shear
cracks (60% < X) for each loading-unloading cycle islisted in Table 1. A total of 100 waveform sets out of
the recorded 184 sets were solvable and could beanalyzed properly.

12th International AE Symposium, Sapporo, JapanIV
rl/ ;//
V v-.-........

/'

I...,...,

r--

I

11/

v

VI VI
11/
I. 1/

VII I

- I /'I)"VI / 1/ /.,.."..

'It:"'I.l:

/

/ ://
m VJI / 1/

1784

I

I

",

1//1 /

Iffl ~ VjJ

IV

0

I

J

/
/

/

/
/

V

1//1. '/ r/

01

03

02

0,4

CRACK WIDTH lmm)
Fig. 6 Relationship between the tensile crack width and the applied load in the bending test.
2500-.-----------------,

=
:I:

2000-

~ 15000::-=------- v-~ 1000~:::>z 500-

o-.......o;=:::::::::;:...-....---....-..--.-_-..,.----.-~
o
~
98
147
196
LOAD (kN)

Fig. 7 Relationship between the number of AE hits and the applied load.
Table I Results of the moment tensor analysis of the bending test.
Cycle
I

n

m
IV
V

Phase
loadingloadingloading
unloadingloading
unloadingloading
unloadingTensile3

Medium
1

Shear

7

7
1
4

18

6

1
2

1
4

4
2

15
3·
7
14

Total
8
2
32
1
25
3
9

20

Shown in Fig. 8 are crack locations projected onto the X-Y and the X-Z planes. Tensile cracks are indicated byarrows (H), the orientation of which corresponds to the crack opening direction. Shear cracks are given by crosses(+). Medium cracks are shown by the combination of the two signs.
It is seen, in these results, that shear cracks have been already initiated near the reinforcing bar shown by brokenlines during the 1st loading. When the Kaiser effect breaks down during the 2nd loading, only shear cracks are817

12th International AE Symposium. Sapporo, Japan

V Hit No. 135~159 (Loading)..~............

V Hit No. 161-184 (Unloading)
I

..

"

. . . . . . . . . • • • • • " ' . " . "f,~" • • • _....................1!.'>Ii}. .__·lt~····_ ••••

Z

.

_

- .

Lx!-,-------=--------..l....-. _

y

_

..~

-- _._. --_ .. - +-. _.. -~\-. - - --I~_..

............ ' ••• _.._ .l_~__.

_..---_.- --.-_..- ..---

L~x-----------'
Fig. 8 Visualization of cracking process during the bending test by the moment tensor analysis.

detected. The ratio of shear cracks are 50% (4/8) in the 1st loading, 56% (18/32) in the 3rd loading, 60% (15125) inthe 4th loading and 78% (719) in the 5th loading. The ratio increases as the breakdown of the Kaiser effect becomes
clearer with the development of the fracture. It is also observed that shear cracks are generated during the 4th and Sthunloading. These are thought to be due to slip between the crack faces of the existing shear cracks.

I unloading

I loading

II loading (1)200

fr~t4)t

I ~~*
~

X

":::~I
--

~

~~

z

Ly
0

100

100

...,..

+/~

$~
x

X

rJ. ).

~1#,
.....
~

Ly

0

--;..

100

Fig. 9 Visualization of cracking process during the bond strength test by the moment tensor analysis

518

12th International AE Symposium, sapporo, Japan

Table 2 Results of the moment tensor analysis of the bond strength test.
Cycle
I

D

Phase

loading
unloadingloading (I)holdloading (2)Tensile3

Medium
5

8
15

5

8
4
6

3
13

Shear
7
10
14
4
23

Total
15

23
37
11

42

3.2 Bond Strength Test
Results of the moment tensor analysis in bond strength tests are given in Table 2 and Fig. 9. A total of 128
waveform sets could be properly analyzed out of 405 sets recorded during the leSt. The specimen was first subjected
to loading-unloading. Then, it was re-loaded with some hold-time dming load increase. Since shear cracks were
produced during the 1st loading as clearly seen in Table 2, the Kaiser effect was not observed during the 2nd loading.
It is indicated in Fig. 9 that tensile cracks are produced near the reinforcement in the early stages. However, they
spread to wider areas in the later stages. An intense AE cluster due to shear cracks is observed around the intetface
between the reinforcement and concrete during the 2nd loading. These shear cracks should be attributed to the slip
occurring at the interface between the reinforcement and concrete.

4. Discussion
Possible AE sources during the fractme of reinforced concrete are: initiation and growth of main tensile cracks,
those of tensile micro-cracks, shear micro-cracks, and mixed mode of both types of cracks produced around theinterface between the reinforcement and concrete. Additionally, mechanical rubbing of the interlocked faces due toslip between repaired part and original concrete and friction of crack faces during loading or unloading should beconsidered.
We have conducted systematic studies (Okamoto et al., 1991; Yuyamaet aI., 1994; Yuyama et aI., 1995) on AE
behavior during the fracture of plain concrete beams, reinforced concrete beams and repaired reinforced concretebeams. It has been shown that:(1) The Kaiser effect exists during the growth of tensile cracks under cyclic loading.
(2) The effect breaks down when the opening width of tensile crack (surface crack) exceeds 0.15-0.20 mm. Thisis because shear cracks start to play the primary role around the interface between the reinforcement and concrete,
giving emissions due to the mechanical rubbing or friction of crack faces during loading and unloading.
In the present work, the item (2) described above has been confirmed by applying the moment tensor analysis to thefracture of concrete specimens. The cyclic bending test shows that the critical crack width for the breakdown of the
Kaiser effect is 0.12 mm, which is slightly smaller than 0.15 mm observed previously.
In evaluating the structural integrity of concrete members, shear crack initiation at the interface between thereinforcement and concrete or that between repaired part and the original concrete is vitally important. Accordingly,
its detection can be a practical criterion to measure the severity of damage induced in concrete. According to thelimit-state design design code in the Japan Society of Civil Engineers (JSCE), the allowable width of surface cracks
is less than 0.15-0.2 mm in the service limit. As has been shown so far, when the opening width of the surface
crack exceeds 0.12 mm, the Kaiser effect starts to break down and high AE activities are observed during unloading.
Therefore. a breakdown of the Kaiser effect and high AE activities during unloading can be very effective indices in
estimating the level of deterioration in concrete structures.

5. Conclusions
In this paper, fracture tests have been conducted on two types of reinforced concrete specimens under cyclicloading. From these results, the following conclusions can be drawn:819

12th Intemational AE Symposium, Sapporo, Japan(I) Cracking process in reinforced concrete can be quantitatively evaluated and visualized by applying a moment
tensor analysis to the AE waveforms detected during the fracture.
(2) Bending test has shown that both tensile and shear cracks are generated around the reinforcement in the earlystages of the fracture. However, the contribution of shear cracks increases as the cracking process progresses.
Finally, it has been found that shear cracks are initiated near the interface between the reinforcement and concreteeven during unloading. It has been also shown that the Kaiser effect starts to break down and high AE activities
are observed during unloading after the opening width of the surface crack has exceeded 0.12 mm.
(3) Bond strength test has found that tensile cracks are produced near the reinforcement in the early stages. They
spread to wider areas in the later stages. An intense AE cluster due to shear cracks has been observed near theinterface between the reinforcement and concrete. These shear cracks are attributed to the slip occurring at theinterface between the reinforcement and concrete.
References
E. Enoki, T. Kishi and S. Kohara (1986), "Determination of Micro-cracking Moment Tensor of Quasi-cleavage
Facet by AE Source Characterization", Progress in Acoustic Emission 1ll, JSNDI, Tokyo, pp. 763-770.
K.Y. Kim and W. Sachse (1984), "Characteristics of AE Signals from Indentation Cracks in Glass", Progress in
Acoustic Emission II, JSNDI, Tokyo, pp. 163-172.
M. Ohtsu (1991), "Simplified Moment Tensor Analysis and Unified Decomposition of Acoustic Emission Source :Application to in Situ Hydrofracturing Test", J. Geophysical Research, 96(4B) April, 6211-6221.
T. Okamoto, T. Ayata, H. Fujiwara, and S. Yuyama (1991), "Discrimination of Cracking Pattern Developed in
Reinforced Concrete Structures by Acoustic Emission", Proc. 4th World Meeting on AE, Sept., Boston, MA,
ASNT. Columbus, OR, pp. 208-214.
S. Yuyama, T. Okamoto and S. Nagataki (J994), "Acoustic Emission Evaluation of Struetural Integrity in Repaired
Reinforced Concrete Beams", Mal Eval., 52(1). 8~90.
S. Yuyama, T. Okamoto, M. Shigeishi and M. Ohtsu (1995), "Acoustic Emission Generated in Reinforced Concrete
L-Frame under Cyclic Loading", Mat. Eval., 53(6), 599-604.

S2D

12th Intemational AE Symposium, Sapporo, JapanThe Interaction between Pore Fluid Pressure
Changes and Crack Damage Evolution in Rocks and
Subsurface Rock Structures Modeled from Acoustic
Emission Data
Peter Sammonds, Philip Meredith, Javier Gomez and Ian Main
Abstract

We present results from laboratory triaxial deformation experiments where the evolution of crack damage has
been followed by continuous monitoring of acoustic emission (AE) output (event rate and event amplitude distributions). Using a fractal model to relate the size distribution of cracks to the power-law amplitude distribution of AE
events. we then calculate the evolution with time of a "damage parameter", from which it is possible to recover boththe stress-strain relation and the crack density evolution describing the deformation history. A novel feature of recent
experiments has been the ability for independent servoconb'Ol of pore fluid pressure and/or volume during deformation. In particular, for the condition where pore fluid volume is maintained constant, we find that deformation is
temporarily stabilized in the post-peak strain softening phase that precedes fault rupture. Stress-strain curves modeledfrom AE data show close correspondence with directly measured curves up to peak stress, including pore pressurechanges. We thus demonstrate how the influence of pore fluids on the deformation behavior and crack damage evolution in rocks can be inferred from remotely measmed AE data.

1. Introduction
Fluids in the crust have a profound influence on the dynamics and evolution of natural sub-sulface reservoirs.
Firstly, there is the mechanical role of pore fluids. which weakens and embrittles rocks. This is usually described interms of the law of effective stress. whereby the hydrostatic component of the stress field (determined by the depth ofburial in the crust) is reduced by an amount equal to the pressure of fluids contained in pores within the rock. Secondly, the chemical activity of pore fluids enables cataclastic deformation to occur. even at low stresses, through thechemical weakening of atomic bonds at the crack tip. This process is called stress corrosion (Meredith and Atkinson.
1983). It is dependent on stress state. temperature and time, and can be described by a power law relationship between
crack growth velocity and stress intensity. At low levels of stress intensity. crack growth is slow and stable. but athigh levels. crack growth accelerates rapidly and becomes dynamic.
In our laboratory we have monitored cataelastic rock deformation by recording acoustic emissions (AE) emiuedby growing microcracks. We have done this for crack growth under tensile loading (Meredith and Atkinson. 1983).
for triaxial compression of dry specimens (Main et at, 1989). and for triaxial compression in the presence of water
as a pore fluid (Sammonds et aI., 1992). At a crustal scale. earthquake nucleation and rupture is accompanied byseismicity. We have sought to interpret earthquake mechanics from our understanding of fracture at the laboratory
scale. and in particular the key role water plays in crustal deformation (Main et aI.• 1989; Sammonds et aI., 1992).

Acoustic emissions are also routinely measured in geothermal reservoirs. in the Tohoku region of Japan as ameans of monitoring and controlling steam production (Niitsuma et at. 1987). The spatial distribution of AE has
been used to monitor crack extension in the reservoir and the rate of steam production has been metered by valves
conttolJed by the AE event rate. It is our aim to provide a more quantitative model for crack growth in subsurface
Received October 20. 1994. P. Sammonds, P. Meredith and J. Gomez are affiliated with Rock and Ice Physics Laboratory,
Research School of Geological and Geophysical Sciences, University College London. London WCIE 6BT. UK and I. Main
is with Department of Geology and Geophysics. University of Edinburgh, West Mains Road, Edinburgh EH9 3JW. UK
Based on a paper that was given at the 12th International Acoustic Emission Symposium. Sapporo, Japan and was includedin the proceedings, Progress in Acoustic Emission VII. JSNDI, Tokyo, Japan.
Journal or Acoustic EmissiOll
Volume 13. Numbers 1/2

S210730-00SOI9S1SS.00I13S21-S28
Copyright <i>199SAcoustic Emissioo Group

12th International AE Symposium, Sapporo, Japan

reservoirs. As a first step. we present in this paper quantitative calculations of the evolution of brittle damage derived
from our laboratory experiments on rock deformation in the presence of pore fluid.

2. Modeling Mierocrack Damage Evolution
AE from microcracking measured during tensile fracture experiments (Meredith and Atkinson. 1983) and triaxial
deformation experiments (Mogi. 1985) on rocks exhibit the same frequency-magnitude distribution as eanhquakes.
This is the log-linear Gutenberg-Richter relation between earthquake. or AE. frequency and magnitude. i.e.•log Nc = a - b(rn -IDe).

(I)

Nc is the number of AE events of magnitude greater than or equal to m in a unit time interval. The event rate for
occunence above a threshold magnitude IDe is N = Nc(ffic)= 10". b is the seismic b-value. the negative gradient of the
log-linear AE frequency-magnitude plot. Our modem explanation for why the Gutenberg-Richter relation is applicable to fracture both on a crustal scale and on a laboratory scale is that rock fracture is fractal process. That is to say
rock fracture results from the evolution of a population of microcracks that has a self-similar dislribution of crack
lengths.
Main (1991) developed a modified Griffith criterion for the evolution of damage due to an array of tensile cracks.
Ignoring the interaction potential between neighboring cracks. Main defines the mean potential strain energy release
rate (<0» per unit crack surface area A by<G>=- <iJUlCJA> =B2<f<c>(2)where U is the elastic strain energy. (J is the stress applied to the boundaJy of each element containing a crack, •sumed uniform. c is the crack semi-length in a volume element and B =nJE. where E is Young's modulus for tensileloading of cracks. For a fractal distribution of crack lengths. Main (1991) showed that mean crack length <c> can becalculated from
(3)

where

=

C.'Co (DN,&:Ico)III~1
and NT is the number of cracks. F(c) is the discrete frequency distribution measuring the number of cracks in thelength range c - &12 < c < c +D is a fractal dimension of the fracture system and is restricted to the range I <D < 3. If seismic moment scales as crack length cubed and the moment-magnitude relation is log-linear with slope
C. then D 3b/C. As the number of cracks is proponional to the number of AE events and D can be infem:d fromb. monitoring AE allows the evolution of <c> and hence <0> to be calculated.

&n..

=

Cox and Meredith (1993) have described a methodology to relate microcrack damage evolution to constitutive
stress-strain behaviour. They calculate an isotropic crack damage parameter. X. from the mean crack length. infeITedfrom AE monitoring. They then use this damage parameter to calculate the effective Young's Modulus. E'. by employing the models of Walsh (1965) and Bruner (1976) for the change in modulus in a cracked solid:
E·w

T=

I
E~
NT < c3 >I+FX' 'E=eltp(-HX). X=
V(4)

where E.,' and Ea' are the Walsh and Bruner effective moduli. respectively. F and H are constant, approximately equal
to 3. V is specimen volume. This provides a complementary approach for calculating a damage parameter to that ofMain.

3. Experiments
We have performed triaxial deformation experiments on initially intact specimens of Darley Dale sandstone.
Right cylindrical specimens 15 mm in diameter by 45 DUD in length. jacketed in a ductile copper sleeve. were c&formed in compression in a high pressure triaxial cell. incorporating a servo-controlled pore fluid pressure intensi-

12th International AE Symposium, Sapporo. Japanfier/volumometer. An all round hydrostatic pressure is first applied to the specimen and maintained at a set value (the"confining pressure"). High pressure water is forced into the specimen through a hole in the upper loading ram by
the pore fluid intensifier. The specimen is left to equilibrate. Then an additional differential axial load is applied to
the rock specimen by a 200 leN servo-controlled actuator at constant displacement rate. Further details of the experimental arrangement can be found in Sammonds et at (1992). During deformation of the specimen the pore fluid intensifier/volumometer can be set to maintain either a constant pore fluid pressure or constant pore fluid volume. byusing either a pressure transducer or displacement transducer to provide the control signal. These conespond to controlled "drained" and "undrained" conditions. AE is detected continuously using a transducer located close to thespecimen in the hollow lower loading ram using a I MHz resonant frequency lithium niobate pressure wave piezoelectric transducer. The signals are filtered. amplified and sent to an AE analyzer. At regular 15 s intervals. the recorded emissions are logged by computer and the analyzer reseL

'==

_24

~

dominates
I

c

0

'E

0-

:I

'"

I II

C

III

>

3000

III

101

<

2000
ID

~

~ 12

txpOIl8ntiaI rise In N:.1'8t8

1000

with onset of cracking ....

0

I~strea~.4SdB

200

IftaJa • 55 dB

2.00

150

-

1.50

0
Q.

2

III

.
Vi

I)
~

100

'0

>

III

I)

I

D

1.00

SO

o
o

500

1000

1500

2000

2500

~~

3000

Time (sec)Fig. I(a) Darley-Dale sandstone specimen deformed under conditions of constant pore fluid volume at a nominal
strain rate of lO,s/s and a confining pressure of 50 MPa. Upper plot: Pore fluid pressure/time curve (continuous line)
and remporal changes in the AE event rate (discontinuous line). Lower plot: Differential slJ'eSsltime curve(continuous line) and temporal changes in b-value (discontinuous line).

12th International AE Symposium, Sapporo, Japan

10

(b)

!

l. 6

300

~.

exponential rise In AS. ratewith cnset of cracking "~.40d8mllliD•

peak stress

50 dB

I I~ stress

200

200

1.50

100

100

~

/
.........................................................................................................................~L.LLL..LL............~...............................

500

1000

1500

2000

2~

O.5O

3000

Time (sec)Fig. 1(b) Darley-Dale sandstone specimen defonned under conditions of constant pore fluid pressure at a nominal rateof 10·'/5 and a confining pressure of SO MPa Upper plot: Pore fluid pressure/time curve (continuous line) and temporal changes in the AE event rate (discontinuous line). Lower plot: Differential stress/time curve (continuous line)
and temporal changes in b-value (discontinuous line).
Figure l(a) shows results from an experiment where a Darley Dale sandstone specimen was defonned in thepresence of water. as a pore fluid, held at constant pore fluid volume. (1bese conditions roughly correspond to adepth of2-3 kIn with a pore fluid pressure that is initially hydrostatic). After a period of stability during initial loading, the pore fluid pressure starts to increase as the specimen is compacted, peaking as the opening of new dilational
microcracks begins to dominate over the closure of pre-existing cracks and flaws, and then falls. It reaches an approximately constant level during the frictional sliding phase. Dynamic failure is preceded by a prolonged period ofstrain softening due to local dilatancy hardening, caused by the falling pore fluid pressure. The AE rate increases exponentially with time, reaching an inflection point around peak stress. Post failure the rate falls off roughly acc0rding to a power law decrease. The b-value initially decreases with specimen defonnation and the experiment reproduces
the now-familiar short-tenn b-value minimum just prior to dynamic failure (Main et al.• 1989). An intennediatetenn b-value minimum is also observed. followed by a recovery. before dipping to the second minimum just prior to12th Intemational AE Symposium, Sapporo. Japan

1
1\

/

C

V

....
1\

C

r

/~

fallure-lSpecimca

SpCcimaa faiIIIrc

~

1\

I

!-

....v1\"
v"

V

t:

III

fl

I~

,.
(vi
0.5

.)

SOO

1000

1500

2000

2500

0.7

3000

..
:l

...... , .~oo

I.,

·cco

,.

--"
I~OO

2000

2500

3000

Time (sec)nme (sec)

Fig. 2 Temporal evolution of...J<G> and mean crack length <c> (data from Fig. la).
the dynamic stress drop. 'This is the double b-value minimum. characteristic of earthquake precursors, that was reponed by Sammonds et aI. (1992). In Fig. l(b) we present results from an experiment conducted under conditions ofconstant pore fluid pressure. 'The application of even a small pore fluid pressure, maintained constant throughout the
test, results in a stress-time curve which shows only a shan sb'ain-softening phase and small dynamic stress drop. A
single b-value minimum is observed just prior to dynamic failure under these conditions.
Our experimental results reveal an exponentially increasing rate of AE during loading under both conditions up
to peak stress. However for the constant pore fluid volume experiment there is an abrupt flattening of the AE ratearound peak stress. 'This we interpret as being caused by local dilatancy hardening reSUlting from falling pore waterpressure, although the specimen is sb'ain softening overall. This has the effect of extending the period of post-peakstress deformation before dynamic failure occurs. A declining b-value is observed initially for anelastic deformation
for both test conditions. For the constant pore fluid pressure experiment the decrease in b-value leads directly to dynamic failure immediately following minimum b-value. Even though overall stress is falling as the specimen sb'ainsoftens this is not sufficient to relieve the stress intensity driving the system to failure. For the constant pore fluid
volume experiment the b-value first recovers before falling to a second minimum at failure. In this case, the combined effects offalling applied stress and falling pore fluid pressure allows a relaxation in stress intensity. Damage
accumulation is still progressing but the formation of the shear fault is delayed.

4. Modeliag Damage Evolatloa from AE Data
We have applied the methodology of Main (described above) to calculate inferred changes in the mean potential
strain energy release rate, <0>, with deformation. These results are shown. for the constant pore fluid volume experiment, shown in Fig. 2. It can be seen that both peak stress and specimen failure correspond with maxima in<0>. Peak stress corresponds to a local maximum in mean crack length, but specimen failure occurs at maximum
mean crack length. Likewise, peak stress corresponds to a local maximum in mean crack length, but specimen failure occurs at maximum mean crack length (Main et aI., 1993).
We have then followed the methodology of Cox and Meredith (1993) (described above) to construct stress-strain
curves from microcrack damage evolution. The stress-strain curves. derived using both the Walsh and Bruner models,
are shown in Fig. 3 for the constant pore fluid volume or "undrained" experiment and constant pore fluid pressure or"drained" experiment (for which the experimental data are given in Fig. 1). The results in Fig. 3 show that the stresssb'ain behavior of the "drained" experiment can be well characterized using AE data. The Bruner self-consistentmethod follows the strain softening phase rather better than the Walsh method. Cox and Meredith also reported agood fit with mechanical daIa for the uniaxial. unconfined, deformation of dry sandstone. However, for the"undrained" experiment, it is clear that in the long period of strain hardening and strain softening the modeling breaks

S25

12th International AE Symposium. Sapporo. Japan,;00,----------------------,ta) Constant pore Quid volume ("undraiDcd") expc:rimeDl
Walsh model

:00
'j

~
~~
:;

in

.....
100

-- - -

O~':'OO"'-K~.....~......OI.".O....IO~......I...I..~......OI.".O....2..1.0~ ................1."0.r...OJ.3....
0 ......1...I.."""""......I.,,O..r..J.040
Strain300,-----------------------......,
Bruner model

200
\
\
100

-- --

..................r..J....I..J,...o...I.........:...&.............I.".r..,.......................&..&....................."'_&....r....I........~

O~:...

0.000

0.010

0.020

0.030

0.040

StrainFig. 3(a) Stress-strain cmves derived from AE daJa for the constant pore fluid volume or "undrained" experiment(shown in Fig. la). Upper plot: Stress-strain curve derived using the Walsh model (solid line). Comparison withmechanical data (dashed line). Lower plot: Suess-strain curve derived using the Bruner model (solid line). Comparison with mechanical data (dashed line).
down. For both the Walsh and Bruner models, the calculated stress falls sharply post-peak stress. when the actUal
mechanical data shows gradual strain softening is occurring.

S. Discussion
Acoustic emission has been used at the Kakkonda geothermal field to monitor and control operations (Niitsuma
et aI., 1987). By analyzing the spatial distribution of AE it has been found that AE sources are concentrated near
fault planes, which Niitsuma et aI. (1987) interpreted as resulting from crack extension during in-service operationand pressure build-up tests (when the well-head is closed). Reservoir stability depends on the amount of flow "shutoff" in the reservoir. However, to optimize steam production. it is important that reservoir instability is controlled.
At the Kakkonda field, this has been achieved by monitoring AE event rate.

12th Intemational AE Symposium, Sapporo, Japan~1:l0,---------------------------'(b) ConsWU pore fluid pressure ("drained") c:xperimcD1
Walsb modcJ
o

.....

~ 200
...,

-

1/1
<II

~

VI

100

0.005

0.010

0.015
Strain0.0.300.020

300~-----------------------'

Bnmermodcl.......

....

o

~200

-

100

OWolo..I..L.I.....w.&...Io.L.Iu.L.u.&.....&..U.~u.L.I-I-I...................u.L.I-I-I...................&..U........o..:..IooI

0.000

0.005

0.010

0.015
Strain

0.020

0.025

0.0.30Fig. 3(b) Stress-strain curves derived from AE data for the constant pore fluid pressure or "drained" experiment(shown in Fig. lb). Upper plot: Stress-strain curve derived using the Walsh model (solid line). Comparison withmechanical data (dashed line). Lower plot: Stress-strain curve derived using the Bruner model (solid line). Comparison with mechanical data (dashed line).
AE monitoring in geothennal reservoirs bas demonstrated the dynamic nature of reservoir response to steam pr0duction and how reservoir instability can be controlled using AE event rate. However. our laboratory experiments
show that along with AE locations and AE event rate, measuring AE magnitudes can provide important information
on crack development in deforming rock in the presence of pore fluid. By measuring the AE frequency-magnitude
disuibution an instantaneous b-value can be calculated. From the number of AE events and the seismic b-vaIue aninferred instantaneous mean crack length. <e>, can be calculated. This method therefore provides a means of quantifying damage by remotely monitoring AE events.
For tensile fracture, deformation is centered on a dominant microcrack and the stress intensity is the relevantmeasured variable. Dynamic failure ocxurs when the stress intensity reaches a critical value, the rock's fracture
toughness (Meredith and Atkinson, 1983). However, for fracture in compression. when brittle deformation is acc0mplished by an evolving ensemble of microcracks, it is necessary to consider temporal changes in the mean strain energy release rate, <0>. <0> is a more useful parameter to consider than stress. In fracture mechanic terms, rock fail-12th International AE Symposium, Sapporo. Japanure is not dependent on applied stress alone, but on crack sizes as well. From <c> and the measured differential
stress, <0> can be calculated. The results from the "undrained" experiment (Fig. 2) shows why <G> is a better parameter to use than stress, as the failure in compression did not occur at peak stress. but after a period of strain softening. Temporal changes in <G> show that its instantaneous value fell post peak stress (Fig. 3), demonstrating theeffectiveness of the local dilatancy hardening mechanism in delaying final failure. However, <G> then rises to a second peak at failure, whilst stress continues to fall.
We have shown that a quantitative analysis of AE data may be used to infer the mechanical behavior of rock undergoing damage in compression in the presence of pore water (Fig. I). Following the approach of Cox and Meredith(1993) we have used an isotropic damage parameter. Our results for the "drained" experiment (Fig. Ib) are wellmodeled by both the Walsh and Broner models, although the self-consistent model (Bruner) provides a better fit in
the strain softening regime than the dilute crack model (Walsh). However for the "undrained" experiment the pr0longed strain softening phase, promoted by local dilatancy hardening, is not well-modeled. The use of an isotropic
damage parameter may be inappropriate here as defonnation could be dominated by highly orientated cracks growing
in a shear zone of intense deformation. An isotropic damage parameter could over-estimate the overall softening
caused by cracking. This is what we observe.

Acknowledgment
The authors thank Professor H. Takahashi and Dr. M. Takanohashi for interesting discussions about geothermal
reservoirs. Financial support was provided in part by the UK NERC. Support from the British Council and the JSPS
has enabled PRS and PGM to visit the Tohoku geothermal program in Japan. PRS is a Royal Society University
Research Fellow. 1G is a Fleming Fellow.

References
W.M. Bruner (1976), "Comment on 'Seismic velocities in dry and saturated meked solid", J. Geophys. Res., 81,
2573-~76.

SJ.D. Cox and P.G. Meredith (1993), "Microcrack formation and material softening in rock measured by monitoring acoustic emissions", Int. J. Rock Mech. Min. Sci. Geomech. Abstr.30, 11-24.
lG. Main (1991), "A modified Griffith criterion for the evolution of damage with a fractal distribution of crack
lengths: application to seismic event rates and b values", Geophys. J. Int, 107, 353-362.
lG. Main, P.G. Meredith and C. Jones (1989), "A re-interpretation of the precursory seismic b-value from a fracture
mechanics model", Geophys. J. Int., 96,131-138.
I.G. Main, P.R. Sammonds and P.G. Meredith (1993) "Application of a modified Griffith criterion to the evolutionof fractal damage during compressional rock failure", Geophys. J. Int., 115, 367-380.
P.G. Meredith and D.K. Atkinson (1983), "Stress corrosion and acoustic emission during tensile crack propagationin Whin sill dolerite and other basic rocks", Geophys. J.R. astr. Soc., 75, 1-21.

K. Mogi (1985), Earthquake Prediction, Academic Press, London.
H. Niitsuma, N. Chubachi and M. Takanohashi (1987), "Acoustic emission analysis of a geothermal resenoir and its
application to resenoir control", Geothermics, 16,47-60.
P.R. Sammonds, P.G. Meredith and lG. Main (1992), "Role of pore fluids in the generation of seismic precursors
to shear fracture", Nature, 359,228-230.
J.B. Walsh (1965), "The effect of cracks on the uniaxial elastic compression of rocks", J. Geophys. Res., 70, 381389.

sa12th International AE Symposium, Sapporo,.Japan

Acoustic Emission Analysis of TiAI Intermetallics

Manabu Enoki and Teruo Kishi
AbstradAcoustic emission (AE) source characterization technique was used to evaluate the microfracture process of TiAl
intennetallics. AE wavefonns from the materials with different microstructure were measured. Material with lamellar
microstructure demonstrated high fracture toughness and also high AE activity during fracture toughness tests. Material with equiaxed microstructure showed low fracture toughness and low AE activity. Nucleation time and size of
microfracture were evaluated. Microfracture process such as microcracking and shear ligament was analyzed from theresults of quantitative microfracture parameters. and nucleation time of each microfracture was used to understand thedifference between static and dynamic fracture toughness.

1. Introdudion
TJAl intennetallic compounds. which demonstrate high specific strength and strength at high temperature c0mpared with TI alloys or superalloys, are expected to be structural materials for high temperature use in the near future.
Remarkable increase of perfonnance is considered possible when these intennetallics are used as engine components
for aircrafts or automobiles. However, these materials are not in practical use because of low ductility at room temperature, low workability, low fracture toughness and so on (Chan and Kim, 1992; Kim, 1989, 1990).

Research on fracture toughness or reliability of these materials has been reported (Mitao et al., 1991; Soboyejo
et ai, 1992; Deve and Evans, 1991; Chan, 1993). Fracture toughness in various environment has to be measured am
the minimum value of fracture toughness should be used as a technical criterion because these materials will be usedas high temperature structural materials. However, like strength and ductility, the fracture toughness seems to beaffected by not only temperature but loading rate as well. Only static fracture toughness has been reported and few
study on dynamic fracture toughness was carried oul
The present paper aims to measure fracture toughness under both static and dynamic conditions and to investigate the fracture mechanism and loading rate effect on fracture toughness of TIAI. TIAl's have duplex microstructuresconsisting of equiaxed y grains and y + Ul lameller grains and exhibit a good balance of mechanical properties.
Acoustic emission (AE) source characterization technique (Enold and Kishi, 1988) is employed during static fracture
toughness test to evaluate the size and time of microcrack generation.

2. Experimental Procedures
TI-48 at% Al materials were used in experiment Ingot was processed by arc melting method and then heattreated in an At atmosphere. All had duplex microsbliCtures, consisting of equiaxed 'Y grain and lameller grain with 'Y+~. The heat treabnent condition of 1423 K x 2 hr provided the volume fraction of y grain (V"f) of about 75%, and1473 K x 30 min and 1523 K x 30 min gave 50% and 25%, respectively. Av~ge grain size of all materials were200-300 JUD.

Static fracture toughness tests were canied out by using the compact tension specimens. Fatigue precracks wereintroduced according to ASTM E399. Fracture toughness test was conducted by using a screw-driven tensile machineat a crosshead speed of 0.5 mmlmin.
Received October 20, 1994. The authors are affiliated with Research Center for Advanced Science and Technology, The University of Tokyo. 4-6.1 Komaba, Meguro-ku, Tokyo 153, Japan. Based on a paper that was given at the 12th International
Acoustic Emission Symposium, Sapporo, Japan and was included in the proceedings, Progress in Acoustic Emission VII,
JSNDI, Tokyo, Japan.
Journal of Acoustic Bmission
Volume 13, Numbers 112

sa073()..OOS0/9SISS.OOI13S29·S34
Copyright 4> 199SAcoustic Emission Group

12th Intemational AE Symposium. Sapporo. Japanx-v Plotter

AE9620AE9620AE9620PrinterFig. 1 Block diagram of static fracture lest and AE measurement.

•

The Cbarpy specimens with the dimensions of 10x lOx 55 mm were used for dynamic fracture toughness tests. Fatigue prec:racks were produced per ASTM
E399. The strain gauge method was used to measure
the dynamic fracture toughness. At fust, relationshipbetween a stress intensity factor and a strain ntea5l1J\Xiby a strain gauge, which is altached near the crack tip.
is calibrated by using static load. Subsequently. impact
test is done and the time-strain curve during the test is
obtained. Crack initiation is found from the onset of a
decn:ase in strain and this strain provides the dynamic
fracture toughness via the calibration.

KIC-o-KId10 - - - - - -........- - -...30
40
50
60
20
Vy/%

....70...

80

Fig. 2 Effect of volume fraction of equiaxed yon static
fracture toughness (K,J and dynamic &actwe toughness

CKrJ·

AE during tests were measured to evaluate microfracture processes of these materials during tests. Figure
I shows the block diagram of static fracture test and AE
measurement. AE transducer with resonant frequency of
500 kHz (PAC. Pica) was used and the threshold levelat transducer was set to 2.5 mV with a deai time of 10
ms. AE signals during tests were digitized at 20 MHz
rate and recorded.

AE soun:e characterization technique was used to evaluate size and generation time of each microcrack (Enoki
and Kishi, 1988). The following shows the procedure of AE source characterization for one channel measurement.
The detected signal of AE, Vet). can be represented by the following equation.
V(t) = S(t) * G(t) * D(t)(1)

where S(t) is the response function of the measuring system. G(t) the dynamic Green's function of the medium ard
D(t) a source function, which shows the features of each mierofracture origin. The symbol * denotes a convolution
integral in time. The combined response of Set) • G(t) can be calibrated by the simulated signal of pencil lead breaking and deconvolution method. A source function of each mierofracture. D(t). can be deconvoluted in frequency d0main from a detected signal. Vet). and calibrated response. Set) • G(t) according to equation (l).

12th International AE Symposium, Sapporo, Japan

If the obtained source function has a step-like function with the maximum intensity of AD and a microcracking occurs in pure tensile mode, the intensity of AD can be formulated as,
M>=(A + 21l) [u] M(2)where Aand Il are Lame constants. [u] is a discontinuity of displacement and M is an area of microcracko Elastic
consideration around a microcrack provides the size of microcrack. a. as

a = 3 (l - 2v) ~D/16 (l - V)2 ce•(3)where v is Poisson ratio and O'e is the tensile stress for microcracking. The obtained size of microcraek from thisprocedure provides a good approximation even if a mode of microcracking is not pure tensile.

E6oo,.-----.....,.----.....,~500

300,.-----...----.....----__-nas 400

KAe=11 MPa"m

~

g 300

~200 •

.

II

~

I.

-:-.
-

I

t;
~;.: ,.,).200• ..,}/~'-"'.
E.8-...,.1a;k

~

Q)

~100
00

-

(J)

10

20

'0100
~
0
(jj 10'-----~2L.0-----J30
Stress intensity factor • K I MPa"m30(a)V'y::75%

Stress intensity factor, K I MPa"m(a) Vy:75%

1000r------~---_

E

4 0 0 , - - - - - - - - -......--.......,

1<AE=11.5MPavm

~aoo

••

(J)

'I

.::e.
~ 600

It

•

...

J
I

(.)

e 400

.....
.......'."".....
~

.

.I-

~

:.

°e'0 200 • • ., ,al'l"'I~""'].~.~-"~,.
(.)

.Jl

.r

~

o0:---~10::-~--:2:'!0~--~30(jj

Stress intensity factor, K I MPa"m(b) Vy:50%~I010·.....----2....101....----~30
Stress intensity factor, K I MPa"m(b)Vr=50%

50rr--...---r--....--.......- - - -E1000,.--------,.--_ _.....,

~ aoc

•

en

.::e.
~

...

60C

§ 40C

·e

o 20C
~

(jj

Stress intensity factor, K I MPa"m••........
.. '.I~.' Ltf
•

(.)

•

••

.I .... ~

,,9

n.

1'1

1·~0--........-~20""-- ........---.l30

Stress intensity factor, K I MPa"m(e) Vy:25%(e)Vr=25%
Fig. 4 Relationship between stress intensity factor
and size of microcracks of duplexed TiAJ.

Fig. 3 Relationship between stress intensity factor andAE events of duplexed TiAJ.

S31

12th Intemational AE Symposium. Sapporo. Japan

3. Results
Figure 2 shows the results of static and dynamic fracture toughness of duplex TiAl. Static fracture toughness ~creased with an increase of the volume fraction of r. that is. the lameller microstructure provides high toughness.
Results of dynamic fracture toughness are also shown in Fig. 2. Dynamic fracture toughness increased with increaseof volume fraction of r. demonstrating the opposite behavior compared with static fracture toughness. The materialsof 25% and 50% of Vr have high dynamic fracture toughness compared with static fracture toughness.
Figure 3 shows a typical relationship between stress intensity factor and cumulative AE events. AE activity increased at about 11 MPa.Jm in all the materials. Total number of AE decreased with increase of Yr. that is. high AE
activity was observed in the materials with higher lameller content. Figures 4 to 6 show the results of AE source
1 0 , - - - - - - -......- - - - - - - - ,

~

CD

,

..
.
I!"~ -,"b

!!
c: 20

•

CD

E
-..
~
c 5
.2
... r .. ~#I
Cii~·.,
I . . ." "
I I•
u
••
~

~

w

.

•

e
~

z

010

« 10

a

20
30
Stress intensity factor. K / MPavm(a) Vy:75%

150 200 250 300 350 400 450 500
Size of microcracks I j.1m(a) Vy:750/0

10 r--------~.-----...,
II)

'§100

~

...........• •-w«

aC.·.~-e~•50. •to ..

~o~Stress intensity factor. K / MPa-Jm~(b) Vy:50%
10 _ - - . . _ - -......----,,....--..

120...-.r-r--r-r-T-r-"'-r--T-'-"""-r-T-r-...,.-,
KIC=27MPa-.Jm

100

III

::l.

~5
a

liCD

-g

e

c:

•
•
. e.:, II jf~
·L~

CD

~ 60

· ...Il.?il
...

. I
••

!! 80

. ....

CD

E

e.. _

w

« 40

•• t' J'

• •

20

Z

~o

~

Stress intensity factor, K / MPa-Jm°~(C) V"(=25%

150 200 250 300 350 400 450 500. Size of microcracks I j.1m(c) Vy::250/0

Fig. 6 Distribution of microcrack sizes of duplexed
TiAl.

Fig. 5 Relationship between stress intensity factor andnucleation time of duplexed TIAl.

S32

12th International AE Symposium, Sapporo, Japan

characterization. Microcracks generated in the beginning were about 112-1 times the grain size. Larger microfr'acture
sizes occurred at higher stress intensity factors. This seems to be due to the coalescence of microcracks in the ligament Finally, the largest microfracture features were generated with crack extension. The relation of crack extension
and microfracture process ofTiAJ is reponed elsewhere (Enold and Kishi, 1995).
The fracture surfaces of TiAI with duplex microstructures were observed by SEM after static and dynamic fracture toughness tests. Fracture surface after static fracture test shows discrete facets with the size of a grain and inclined from the main crack extension direction by some angles. These facets are considered to be microcracks parallel
to laminates in the lameller grains. Many such facets were observed in the materials with high lameller contents, thenumber of which corresponds to the tendency of total AE events. However, such facets due to microcracking were
not observed in fracture surfaces after dynamic fracture toughness tests, that is. many microcracks were generated
under static loading and the main crack propagated independent of lameller direction and through lameller microstructure.

4. Discussion
The materials with high lameller contents have high static fracture toughness. In these materials many secondary
microcracks are generated separately from the main crack before the crack extension. Such a microcrack, shown in
Fig. 3, controls the microfracture process and fracture toughness of the materials having lameller microstructures.
The coalescence of the microcracks in the direction of a main crack extension provides an enhancement of fracture
toughness, which are shown in Fig. 4 as apparent large size microfraetures.
Fracture toughness of TIAl with lameller microstructure is controlled by the generation of microcracks and sequent shear ligament fracture as mentioned above. Decrease of dynamic fracture toughness in low Vy materials canbe understood by the time of generation of each microcrack in the same way as discussed in the previous paper(Enoki and Kishi, 1995). The time of microcrack generation was evaluated by AE source characterization technique.
The time of microcrack generation is estimated as 2-5 ~; that is. this period is needed to generate a single microcrack. It takes 60-80 fJS from the onset of microcrack generation to the extension of a main crack during the static
fracture toughness test where dKidt equals to about 10"1 MPavmls. On the other hand, it takes only about 10-15 J.ls
for the stress intensity factor at the stan of microcrack generation to the critical stress intensity factor for the extension of a main crack during the dynamic fracture toughness test where dKldt equals to about 1(j MPa..Jm/s. Thus,
there is an adequate time to generate microcracks and to their coalescence via shear ligament during static fracture
toughness tests. However, almost no time exists to generate microfractures during a dynamic test. These are schematically shown in Fig. 7. Consequently. a toughening mechanism of microcrackinglshear ligament provides a highenhancement of toughness in low Vy materials during static fracture toughness test, but a low fmcture toughness isobtained during dynamic fracture toughness test because of loss of the effect of shear ligament toughening.

E

Static fracture toughness testE

~ 40,.....-----------.,

~

~

~

a.

.o..

'0
ctl

>.

00

~ KA

••

~~~::~~~
100
Time Is

.5

en
en

e

200 en0 L---r~~-.....L...J:---'-.-::::-=--~ 0
0 :+.. ~50
100
10-15J,Ls Time /IJ.S

Fig. 7 Schematics of stress intensity factor versus time in the static and dynamic fracture toughness tests.

S33

~

500:;

c:

c:

ene

Kid

'0

en

~KAE

-~...

-- 2

-~ 20
.E
en
en

a.

Dynamic fracture toughness test
40
1000

ctl

.9

12th Intemational AE Symposium, Sapporo, Japans. Condusions
AE during the static fracture toughness tests ofTiAl with duplex microfracture was measured to consider the rate
effect on the fracture toughness and the foJlowing conclusions were obtained.
(1) High static fracture toughness was obtained in the materials with low volume fraction of y because of the generation of many microcracks and subsequent shear ligament fracture during static fracture toughness test.

(2) The decrease of dynamic fracture toughness was observed in the materials with low volume fraction of y becauseof the loss of the shear ligament toughening mechanism due to the lack of time for microcrack generation.
(3) Static fracture toughness in the materials with high lameller contents cannot be used as a practical criterion of

fracture because the toughness decreases at high loading rates.
References
K..S. Chan (1993), Metal. Trans. A, 24A. 569.
K.. S. Chan and Y.-W. Kim (1992), Metal), Trans. A, 23A, 1663.
H.E. Deve and A.G. Evans (1991), Acta Metall. Mater., 39, 1171.
M. Enoki and T. Kishi (1988). Int. J. Fracture, 38,295.
M. Enoki and T. Kishi (1995), Mater. Sci. Engr., in press.
Y.-W. Kim (1990), Microstructure Property Relationships in Titanium Alminides and Alloys, eds. Y.-W. Kim and
R. R. Boyer, TMS-AlME. Wanendale, PAt p. 91.
Y.-W. Kim (1989), J. Metals. 41, 24.
S. Mitao. S. Tsuyama and K.. Minakawa (1991), Mater. Sci. Engr., Al48, 51.
W.O. Soboyejo, D.S. Schwartz and S.M. Sastry (1992). Metall. Trans. A, 23A, 2039.

S34

12th International AE Symposium, Sapporo, Japan

Recent Applications of Acoustic Emission Testing for
Plant Equipment
Masashi Amaya
Abstract
AE testing of used plant equipment was conducted to requalify the structural integrity. Using a measurement
system with a high data acquisition speed, acoustic emission (AE) testing was continued with a low threshold level
and high sensitivity even during plant operation. Correlation analysis between two AE parameters is effective for theelimination of various plant operation noises caused by process fluid. structural friction. environment, etc. Overall
structural integrity is recognized by AE testing. Two recent examples are presented in this paper.

1. Introduction
Acoustic emission (AE) can be a reliable tool for the on-stream inspection (OSI) of process plant equipment. It
is excellent for monitoring and assuring the total integrity of equipment. Acoustic emission testing in general isapplied in the following situations:(1) Hydrostatic or leak testing during shut-down maintenance of eqUipment in service.
(2) Plant start-up after shutdown. and(3) During normal operation.
The major fraction of our experience is in the first category of hydrostatic or leak testing.
Discrimination of noise from signal is the most important and difficult task in the detailed analysis of received
data. This paper shows that correlation analysis of AE parameters is very effective in discriminating some types ofnoise caused by fluid and friction. An AE testing with a relatively low threshold level can be used under severe noise
conditions of plant operation using the correlation analysis (Amaya and Nakano. 1993).
The purposes of having acoustic emission tests for plant equipment is as follows:( I ) To ensure safety during the test, and(2) To requalify the structural integrity of the pressure vessel and other equipment to be examined.
Even if there is no gross defect when the equipment is put in operation various defects could occur or develop during
operation because of temperature. pressure, and environmental conditions, or a defect that was small and not detected
before operation but has since grown. Also, due to restriction in accessing the vessel, there could be parts where theusual nondestructive testing would be difficult or impossible. We perform approximately ten AE testing in plant
equipment such as pressure vessels, chemical reactors, heat exchangers or pipes over a typical one-year period. Some
recent applications are aimed at AE testing during on-stream inspection to take advantage of government recognition(Fowler, 1992; Nakano, 1986).

2. Examples of AE Testing
AE testing was conducted during plant start-up after maintenance shutdown on two hydro-desulfurization reactors
in a refinery. The plant start-up period is appropriate for AE testing because both pressure and temperature are
increasing. Table 1 gives summary of tested reactors. Figure 1 shows an outline of AE testing. Both reactors tested
have been used for more than ten years (Katsuyama et aJ., 1994).
Received October 20, 1994. The author is affiliated with Advanced Technology Center. Chiyoda Corporation. 3-13
Moriyacho. Kanagawa.Jcu. Yokohama. 221 Japan. Based on a paper that was given at the 12th International Acoustic
Emission Symposium, Sapporo, Japan and was included in the proceedings, Progress in Acoustic Emission VII. JSNDl,
Tokyo. Japan.

Journal of Acoustic Emission
Volume 13. Numbers 1/2

S3S

0730-00SOI9SJS's.00ll3S3S-S41

Copyright OI99SAcoustic: Emission Group

12th International AE Symposium, sapporo, Japan
Table I SuJ1UJlaJ)' of tested equipment
Reactor A
Outer diameter (mm)Length (mm)Thickness (mm)3,302

10,00010,000151

126

Material
Design Pressure (kglcm 2)
Design Temperatw'e (OC)1-1I4Cr - II2Mo
101
430

Reactor A

Reactor B

IE. sensors

lE.aensora(18ch)(18ch)

ReactorB

2,952

1-l/4Cr - II2Mo
96
420

Chart Recorder

Pressure & Tempreture

Control room ---'--';;";';;'~~:;"':"':~;';';;';'~--_--I

Fig. I Outline of AE testing.
Table 2 General specifications of Chiyoda Acoustic Emission Analyzing System (C-AEAS).
AESensor
PZT piezoelectric ceramics
Element:
Resonant frequency 200 kHz
Type:Room temperature service and high temperature service(integrated waveguide and preamplifier type)
Preamplifier
40 dB (10 kHz - 1.5 MHz)Gain:
AE Signal Processor
16
Max. AE channels:
4 (10 V full scale)Max. Analog channels:
5,000 events/sec (Max)
Data acquisition:
Main amplifier
0- 40 dB (10 kHz -1.5 MHz)Gain:
AE event, AE energy. Ring-down count
AE Parameters:
Peak amplitude, Rise time. Duration
Data Processing Computer
40 MB hard disk capable of recording 2 million event data
Data storage:
Menu driven, Mouse controlled
Software:23 Color Graphics, Real time and Off-line analysis

S36

12th Intemational AE Symposium, Sapporo, Japan
Analog Signal
Integrated IE. Sensor

IE. Signal Proce88or

AudIo Monitor

Piezoelectricelement

Pulse Generator

Max: 5000events/8ec.

Control Signal

WaveGuide
Personal Computer

Vessel Surface

Fig. 2 Schematic diagram of the C-AEAS.
The reactors tested were connected in series and the AE testing conducted on both reactors simultaneously. Two
16 channel AE measurement systems (C-AEAS, Chiyoda Acoustic Emission Analyzing System) were used. Sixteen
sensors were mounted on each reactor. Table 2 lists the general specifications and Fig. 2 shows a schematic diagramof the C-AEAS which has the major advantage of high speed data acqUisition (5000 eventsls).

3. Results and Discussion
The cumulative AE events, temperature and pressure changes of a typical channel are shown in Fig. 3. The
period of AE testing was approximately 60 hours, from initial startup until a steady state condition of nannal
operation was reached. In AE testing during plant operation, many AE events detected are caused by process fluid.
The detected signal level change is shown in Fig. 4. One noise reduction method is to increase the threshold level;
however. it decreases the sensitivity for AE signals. On the other hand the data acquisition speed of the measmement
system limits the threshold level at which many signals can be detected. The C-AEAS has a high speed with a low
threshold level and high sensitivity even during plant operation when the data acquired contains noise. In this casecorrelation analysis between two AE parameters would be an effective noise reduction method.
A correlation analysis between peak amplitude and duration is shown in Fig. S. Based on our experience. thedata is divided into three areas; area 'A' represents important AE signals, area 'B' is mainly fluid noise and area 'C' ismainly friction noise. Noise reduction software deletes the data in areas '8' and 'C', Examples of source location
maps before and after noise reduction are shown in Figs. 6a and 6b. respectively. The AE source location results
after noise reduction for two reactors are shown in Fig. 7a (Reactor A) and 7b (Reactor B). Evaluation criteria used

for the AE testing are shown in Table 3.
Several concentrations of AE source locations appeared near the insulation support ring in Reactor A (Fig. 7a).
Most of these source locations were caused by friction noise that the software filter passed. but these are not due toserious defects. Very few source locations were generated near a weld line; therefore. it was concluded that emission
sources in the Reactor A are structurally insignificant. Three marked concentrations of source location appeared near
the weld line in Reactor B (Fig. 7b). However. these concentrations were very small and had low energy. Thus. they
are graded as 'C' based on Table 3.

s:n12th Intemational AE Symposium, Sapporo, Japan

40000
~c<

u ...

30000

uE:.

20000

~~
~ ~
.~

30000

-c;

e

a

!iei'

5 ...

:;

10000

20000

t~
~~

uE:.

>
.:::

0

300

10000

at

"3

e

a

200

0

kglcm2

80
60

40

:

20

o

o

:

.

'"

.

1.0
2.0
Time (sec)

3.0 -lOs

Fig. 3 Cumulative AE evenlS, temperature and pressure changes during the AE
testing. which was conducted dming plant start-up after shutdown.

Fig. 4 Detected changes in signal level dming a 90 min. period for 13 of 16 channels.

S38

12th Intemational AE Symposium, Sapporo, Japan

[I I

J

c
3.n
x WI

usee

Duration

5.0

x 1IJ3Fig. 5 Correlation analysis between peak amplitude and duration.

x = 1159.0 V = 1290.0

12.. f IJ ~•• '• .: • •

I.:
I...
• .-

I• • •:: ",'. :.:••' .•'; ", 'J>: ',: ': • .' '\.
•::f."~'•.1.

x = 1159.0 V= 1290.0

12

11

1_

II • • ' , - ••• . . ~. q.. ,. ' . ~-c, I I .. "• ";'""".,- - .' ' . . . fI\'l~ I"'-·~.I··:- .~.,:<~~~' .,' ,~ ': :.
..••.
":'~ ..:1. 'Ji~~\.,,",....',-..~ '" ,. ..: .
:.:.~) ~":~.'I, ':',:."'.!' :: ••
I,

•

.. '

•

• • ••t.

•..

~. ~~ ,~. ~ 'oL..

~.., '4. •...:'!.Itl f. . . . . . . . ·:~:)')~JI. . .\._
~J....,'T.~ '.i).'

•

)

.:

I flO ••• .. '.~. '. "I; J~~ 'f.~'••. ' . : ' _.~.~. •• ~ • ~~1,0•• :~ ••••• ~~.(~.

'.

J~"') •...

..,.

~u:l:S:: ... ',r:.n,,', ,~, .' ",.
. 'I~'• .".~ F",:.' •.-.
.'•• "py• ..... if. ' -.a, .'i....-:, ..'" . • • ~'.I'"
•

II

. .,'
..
1-· •• ' ••

I.

,

.
.-'

..

.,

•

:;

..-,

••

~.

•

r

.

.'.. . ".'-:.
• ',_

.

.

~ f· ..

••:.- •••'."J.:'I1·~'f.::.'.1 I..
..
,V.
',,' ",•·ts·...
...... .~-.......
~"'~A.··· .
~I,

•

•

11

-.., ..

.
'.

.~.

-

..... ..
..- .........

......

\-~,.
..••

~

I

..

16

$----------I-------~!!1

15

16

Fig. 6(a) AE source location map (raw data).

15(b) AE source location map (noise reduced; using thedata from only area A).

The object of AE testing of plant equipments is not to define any small defects but to confinn global structural
integrity. 1l1is is confinned in the two tests in which only insignificant emissions were found. This is important andvaluable. Early warning of developing defects and orderly scheduled repairs are important benefits of AE testing.

References
M. Amaya and M. Nakano (1993), "Recent AET for plant Equipments", 9th National Conference on Acoustic
Emission, JSNDI, Tokyo (in Japanese).

S39

12th IntemationaJ AE Symposium. Sapporo. Japan

Table 3 Evaluation criteria of AE testing for plant equipments
Grade

AE activity

AEenergy

A

Major

High

High

B

Significant

MiddleMiddle

C

Minor

Low

Low

Insignificant

Insignificant

Insignificant

Insignificant

WL

TOP TL

INS, SUP,

0'

Concentration of
AE source location

210'

315'

180'

225'

I

Recommended Action
Immediate shutdown andnondestructive examination (NOE).
Requires follow-up evaluation orcomplementary NOE.
Note for future reference.
Visually inspect accessible areas.
Emission source is structurally
insignificant.
90'

135'

I

_...........1"" '"""".jr~·-:J~~ll· T

WP'~

1 .ci P4I

.ct 1"3,I

0'

60' ~5'I~ r>-. .,INS. SUP, ~i(f'tf'~. b",Z1. ..... 'r

'

LFJ

... .

..:,~~CI O'.

t - -.........- I I - - - .. - -

.

~

'-'

~~

o•

',ii 1 ".
FJ ..

. f'",-'0

WL I----+----+----+.--:",---+----+-""---+--~__t:--_l-........

_. _.__..... l--:~-\----lI----I ..l4l~l)IPI~... _-t -_. ----1----':·:::"."-n-INS, SUP,..... t'~

• •

~f·

:'.i

1

;'CJlIJ'..

........

.~ "
1.-

, .

~

.

•

~.

"

-.

'.
: o....

0

~.

.
"

INS, SUP.

..'. .

I .

j

..

:

~

:

.

.. ": ."

-....
"0

."

.',

WL J---,.til'llrlrll~J~,Oro=o--+---'1'U"fIt;Hf:Urr-)----t--..,~'lltTJ4r---;--:---'ll'II't1(;IJ~Jf'J"""":;:s--'-t

1==::=;jI!t:~rotlq>~~I~=:=i,!I::==~,===:::nJ::::::===;:,=====:I!~c:===I(300')

I
I
I
I
I
I

I
I
I
I
I
I

I
I
I
I
I
I

INShTfiUtllm2??a~~~~~!m:~rIlamz~fl£~fl£~~ifl&l~~~7/,~w.:~.~~~~~~~_
WL "---..;I

I~---------

Fig. 7(a) AE source location (noise reduced) and equipment drawing of Reactor A.

..-121h Intemational AE Symposium, sapporo, Japan

~
0'
til

CI 4

iJ rt ". I ..,,; 3 .
': .

ILl}:

135'

90'

60' 4S'

ell 2

J'l

p~a

0'

5!

;'.

..
--: -"-~rf-'--.

-1-

180'

210'

INS'rortt

I.

m'

315'

•

.:- \.:-~'.

.- 1'--: - - - I ...
..

..:..

.0,

.,
'.'
..
•
.....
.--H· J._'-'--+--_.......-1.~li'~lt--_ _-t-_-:-t~:~.·ll-t.-:... _.. _.-"'_:::1':'~: __:::..:'' r;t',"~ji_·_:_·,_"-:-~I_

INS. SUP. '." ....

.ClIO

Cl11-

.. •

::'-~'"
I.

r

'

..

..

:.:.

.

. ' :..

.

'C11 6".• ~.'~ : ....: '\~.'
.:.

:'.

·'0 .. ',.:::"~. . . --:"", 1 • ',:.
. 0 - ....
. ", : .... ", ...... "
•

·0

°

>:

.' .,..: '.' . .. f~ b _5 .. {••.. ' .. \ • •

.

. "

• ~

•

~:." ~ :

,.

..0:

0

0

-:;....

...... :~--.. .:".- ...... ':.-~ -.-~~-1~I- -

•••••

•

0

••.••

_

H-""'---='-='9"':=-=,.;;,,;,;:;:..t=-=~"'-=-Ijf '~" " ,ItIs. ~L~-=~::'~' ~l¢:==::t;=::;:=1:==~~;::~:t===~=:;:::::t:=~=t.',,',
~.'"
. (~
.
: "
'"
, .

-

.~.

• ..' ' . 1-:-:.:~..""".-..--rf----1--ltr----t----lti-----t--1~.1!.I--;~.~~.'-:C1 '.2 .... '.
II
10
°Cl9

a

a

b

T
~
.... " . .. ..'' .
" . ',' -<I:\.
:;;1
':'-"
. -: '~I'I-f
INS. sup. 12:.:.....-.A--J~.;;:=u~. !.:;.;4.:=•• t=:.:;;:=:t::,=.. :;:;=+=:";:;;::'::':-l=:::='~:+:..=,::;,;..
,

"0

.~\.

~

0'. . .

=..

°

2 . . :_1 .

Ilt--~~-t--....-_t---......._t_---_t_---i_--_1I_'_---_t-~--_l

CII 13'-------t--------4--------I-

81M n l - - - - - - -.......

Wl.'--------....:...--------L-------..:.-...L-

Fig. 7(b) AE source location (noise reduced) and equipment drawing of Reactor B. The three areas indicated by thearrow are concentrations of AE source locations.

TJ. Fowler (1992), "AET·a mature technology for chemical industry safety", Progress in Acoustic Emission VI,
JSNDI, Tokyo, pp. 243-250.
T.J. Fowler (1984), "AET of Chemical Process Industry Vessels", Progress in Acoustic Emission II, JSNDI,
Tokyo,pp.421~9.

K. Katsuyama ct. aI. (1994), "Application of AE technology for field engineers",lPC, Japan (in Japanese).
M. Nakano (1986), "Diagnosis and monitoring of pressure vessels by Acoustic Emission", CHIYODA Corp.,
Tokyo.

S41

12th International AE Symposium. Sapporo, Japan

Effects of Soil Acidity on Acoustic Emission Properties of Sugi (Cryptomeria Japonica) Seedling
Keiichi Sato, Atsushi Uchiyama, Takeshi lzuta, Makoto Miwa, Naoaki
Watanabe, Takafumi Kubo and Masami Fushitani
Abstract
The soil acidified by the acid precipitation is expected to cause water stress to trees. In this work. AE measmement of 2 years old seedlings of sugi (Cryplomeria Japonica D.Don) planted in soil acidified artificially was performed. and the characteristics of generated AE are discussed. There was no AE signals detected during night. cloudy
or rainy day when the intensity of solar radiation was low. The AE generation from a healthy seedling in the control
was concentrated at the SIart of solar radiation when the initiation of transpiration stream caused the cavitation in thexylem. For the seedlings under the condition of water stress caused by transplanting or soil acidification, the AE
generation had a low concentration at the start of solar radiation, and it was spread over the period of the sunshine.
1. Introduction
In recent years. the forest damage becomes a societal problem around the world and acid rain is one of the causes.
The damage given to forest by the acid rain is classified roughly into direct influence and indirect influence throughthe soil on plant. In the latter case. when the acid rain goes down exceeding the neutralization capability of calciumin the soil, salts of such elements as Ca, K. Mg in the soil costs elution and pH of soil falls. and stagnation of activity of soil microorganism delays the decomposition of organic compounds in the soil and disturbs the circulation
system. Furthermore. harmful metal such as AI costs elution and deteriorates physiological function of root and inhibits water absorption of the tree. Through these effects, the acid rain causes the water stress to trees.

It is known that cavitation is generated with the water stress of trees, which is a phenomenon interrupting liquidin the tissue of water transport such as vessels and uacheids in the tree. Milburn (J973a) reported that AE was generated by cavitation in a leaf of Ricinus communis plant. And he found that AE occum:d in xylem by the cavitation
when the plant was subjected to water stress by withholding water and cooling root (Milburn. 1973b). Tyree et al.
(1984) measured AE from a stem of Thuja occidentalis in a pressure chamber and examined it for the relation of AE
generation to water potential in xylem. Sandford and Grace (1985) investigated AE characteristics with cavitation by
cutting a branch and a stem of Malus sylveslris and Chamaecyparis Iawsoniana. Pena and Grace (1986) gave water
stress to Pinus sylveslris planted in a pot by simulated drought in glasshouse and reported the relationship between
the water potential of leaf and the AE count rate. And. Tyree et al. (1986) monitored AE of xylem cavitation of Zea
mays in field condition.
In this studies, considering that acid rain causes the soil acidity and it gives water stress to a tree, AE from 2year-old seedling of sugi (Cryplomeria japonica) planted in acid soil was measured for 12 weeks and deIected AE
characteristics are discussed.

2. Experimental Procedures
Three conditions of artificially acidified soil were prepared for the experiment, in which sulfuric acid solution of
JOO ml containing H+ ion of 10, 20. 30 mg equivalent, respectively, 8fiIed to brown forest soil of 1 liter. The H+
was not added to the control soil. The pH of the control soil was 4.12 at the initiation of the experiment. In 3 condi

Received October 20. 1994. The authors are affiliated with Faculty of Agriculture. Tokyo University of Agriculture andTechnology. Fuchu. Tokyo 183. Japan. Based on a paper that was given at the 12th International Acoustic Emission Symposium. Sapporo. Japan and was included in the proceedings, Progress in Acoustic Emission VlJ. JSNDI. Tokyo. Japan.

Joumal or Acoustic: Emission
Volume 13. Numbers 1/2

S42

073o-<lOS0J9S1SS.00I13S42·S46
Copyright OI99SAc:oustic: Emission Group

12th International AE Symposium, Sapporo, Japan

".

-,.

.

".

~·'~~~~lll~'lM:I".,~~,~~~·t~'~_'_ "'~.'ffi'::J'f~,i'~~?1~ U~~~&k.Fig. 2 AE sensors and seedlings for the experiment.

Fig. I AE sensor set at stem of seedling.

5 0 . - - - - - - - - - - - - - - - - - - , I 00
Relath'e humidty- - '-

, 0

80

\

\

S1

[

e 20

~

r--_-

Temperature

-t..

U.li

0.5

>.

\

'F::l 30

II.;

60

:;

i

=
.l:

I

u

40

~
III

ij

=:

0.1

o

036

"
9

I 2

I 5

I 8

2 I

0
2 4

.......
c:
.:2
ii

:;

...
-="
...
0.2
II

WI

..
..c:
.5"

0
>.

Wi

0.1

....

E

~

0.3

20

".oI.uadlatlon-.

0

TIme or day (hour)Fig. 3 Transition of temperature, relative humidity and intensity of solar radiation on June 22 (fair weather).
tions of acid soil, it was 4.10, 3.97 and 3.85. respectively. A 2-year-old seedling of Japanese ceder sugi (Cryplomeria
japonica D.Don) was transplanted into a 500 ml vinyl pot filling with each soil. It grew in a glasshouse in the University Farm of Tokyo University of Agricuture and Technology for 12 weeks from June 9 until September I, 1993.
A micro-AE-sensor (NAIS S304J.1. resonance frequency of 300 kHz. diameter of 3 mm) was set at a position of
2 em high on the stem of each seedling with silicone grease as a coupler and it was wound with gauze for holding.
The AE signal was amplified with a pre-amplifier (PAC 1220A. 60 dB) and sent to a 4-ehannel AE analyzer (PAC3400) set in a hut next to the glasshouse by 50 m long cables and AE parameters were measured. The gain of theamplifier and the threshold voltage were set at night to detect no noise when AE was not generated from plant body.
Temperature. relative humidity and intensity of solar radiation in the glasshouse were mea..o;ured every hour.

3. Results and Discussion
Figure 2 shows the changes in temperature, humidity and intensity of solar radiation in the glasshouse on June
22. a fair weather day. Figures 3 to 5 show AE energy generated from each seedling in the control, acid soil I andacid soil 3. respectively. Figures 6 to 9 show the changes in temperature, humidity and intensity of solar radiation,
AE energy generated from the seedling in the control. acid soil I. acid soil 3 on July 10. a cloudy day.

sa

12th International AE Symposium, Sapporo, Japan
3 0 0 ......- - - - - - - - - - - - - - - . ,3 00,--------------_-,
Amplitude: SO dB
Threshold: 4.9 V

2 5 0

2 5 0

Amplitude: SO dB
Threshold: 3.4 V

20 0

2 0 0
•

1

..

.~

bl501-

c"

150

II

C

....
.....
' .'

"

~ I 0 0

II:.:.I

< I 000.' .~ •..• "; ,.. ". ,.)~
.
..

5 0

I

5 0

0 ••• ,::.:.

o
o

3

I

'.1

6

9

:~,.: J.~ '.
12

I

15

.'

o

1

18

21

.;. .' __, '.' I

o

24

3

6

9

Time of day (hour)

12

IS

18

21

24

Time of day (hour)Fig. 4 AE energy generated from control seedling on
June 22.

Fig. 5 AE energy generated from seedling in acid soil
I (pH 4.10) on June 22.

S 0 0 ......- - - - - - - - - - - - - - - - - ,
I 00

5 0

Amplitude: SO dB
Threshold: 4.3 V- ....

II.';';;-

R~llltlvr humidlY

250

• 0

,,-

l
"ii" 3 0

6 0~

eo 1 5 0

t-

"

~

40

8 20 Temperolure

c:
,g

E

0.1

:;

Il

11.3

...1

:g

~

...

Ii

a:

'""

1 0 0

';

fJ.2

fJ.1

50

. ..",:':

0

0
0

~

6

9

I

~

I 5

I 8

2 I

fJ

2 4

Time or day lhour)• 0·:' ..: • • "Fig. 7 Changes in temperature, relative humidity andinlensity of solar radiation on July 10 (cloudy day).

Since seedlings transplanted into pots on June 8 received water stress for I to 2 week till new root hair grew sufficiently, they were shaded by a net for 10 days to control direct rays of the sun. It was probable that the seedlings
kept water stress on June 22. The AE generation from the seedling in the control (Fig. 4) and one in the acid soil 3(Fig. 6) showed a similar tendency to each other and appeared in periods of high intensity of the solar radiation. In
Fig. 5 (acid soil I), the AE event is comparatively few and the proportion of AE generation in the afternoon werehigher.
There wac; scarcely any AE generation at night. on cloudy or rain day when there was no or lillie solar radiation.
There was a limited intensity of solar radiation on a cloudy day (July 10) as shown in Fig. 7. Accordingly, a slight
AE generation was recognized in Figs. 8-10.
The water transport rate sensitively responds to a change in the intensity of the solar radiation in a small tree ora seedling, because the xylem volume is small with which water is stored. In the case of a healthy seedling. the cavitation occurs in a period from the initiation of transpiration by the solar radiation until water supply from a root
reaches an adequate rate. Subsequently, when the water absorption at the root balances with the transpiration at theleaf. the water transportation maintains at a fixed rate without cavitation. Since the competence of the water absorp-

S44

..
...

0

t-

-:c

~ 0

10

~

u.,;

.a

~

"c

~

~

i1

200

E

H.ll

80

,../

!

!

12th Intemational AE Symposium. Sapporo, Japan

300.....----------------.

300.....----------------.
AmpUtude: 26 dB

2 5 0

230

200

200

Amplitude: 48 dB
Threshold: 3.3 V

Threshold: 3.3 V~ 1 SO~ 150 •
u

c:

u

c:

=! I 00 •u=!IOOr-so

5 0
Olo...----I_.........

_--Uo..:-~_

o

3

6

9

12

......

15

OIo...--..JL.--.l_........._..:..L_.....I.._..a..._..L-..;....J...L..-~

18

21

o

24

3

6

9

12

15

18

21

24

Time of clay (hoW')

TIme of clay (hOW')

Fig. 8 AE energy generated from control seedling on
July 10.

Fig. 9 AE energy generated from seedling in acid soil
I (pH 4.10) on July 10.

300.....----------------,
Amplitude: 41 dB
Threshold: 3.3 V

230
200

to 1 5 0IICII=!IOO5 0r-o L---1'---L_ _..L...o.......
.. .L,_.J.-,--J'L.-_..L..
'---'
o
3
6
9
12
15
18
21
24
TIme of day (hOW')

Fig. 10 AE energy generated from seedling in acid soil 3 (pH 3.85) on July 10:tion at a root deteriorates in the seedling just after transplantation or in the acid soil. the cavitation also occurs at thestart of transpiration stream by the initiation of solar radiation. If the plant finds that it is under the condition of water stress without satisfactory water supply from the root. it closes the stomata on the leaves in order to control thetranspiration. When the plant is released from the water sttess with normal xylem pressure potential. it tries to open
the stomata in order to begin the transpiration. However. the cavitation is generated again and the plant must close
the stomata to stop the transpiration stream for lack of the water supply. Therefore. the cavitation occurs after thestart of the solar radiation in the water-sttessed seedling.

4. Conclusion
The AE detected from 2-year-old seedlings of sugi (Cryptomeria japonica) planted in the soil acidified artificially
was examined. There was scarcely any AE generation at night. on a cloudy or rainy day when there was little or nosolar radiation. The AE generation of a healthy seedling in the control was concentrated at the initiation of the solar
radiation. In the case of seedlings water sb'eSSed by transplanting or soil acidification. the AE generation had low

S4S

12th Intemational AE Symposium, Sapporo, Japan

concentration at the start of the solar radiation, and it was spread over the period of the sunshine. Therefore, AE generated with the cavitation in plants may be related closely to the transpiration at the leaf and the water absorption at
the root.
References
I.A. Milburn (1973a), "Cavitation in Ricinus by Acoustic Detection: Induction in Excised Leaves by Various Fac-

tors", Plant&, 110, 253-265.
lA. Milburn (l973b), "Cavitation Studies on Whole Ricinus Plants by Acoustic Detection", Planta, 112,333-342.
M.T. Tyree, M.A. Dixon, and R.G. Thompson (1984), "Ultrasonic Acoustic Emission from the Sapwood of Thuja
occidentalis Measured inside a Pressure Bomb", Plant Physiol., 74, 1046-1049.
A.P. Sandford and J. Grace (1985), "The Measurement and Interpretation of Ultrasound from Woody Stems", J. Experi. Botany, 36(163),298-311.
1. PeDa and 1. Grace (1986), "Water Relations and Ultrasound Emissions of Pinus Sylvestris L. Before, During ml
After a Period of Water Stress", New Phytol., 103,515-524.
M.T. Tyree, E.L. Fiscus, S.D. Wullschleger, and M.A. Dixon (1986), ''Detection of Xylem Cavitation in Com
under Field Conditions", Plant Physiol., 82, 597-599.

S46

12th International AE Symposium, Sapporo, Japan

Acoustic Emission of Bending Fatigue Process of
Spur Gear Teeth
Kouitsu Miyachika, Satoshi Oda and Takao Koide
Abstract
This paper presents a study on acoustic emission (AE) in the bending fatigue process of spur gear teeth. Research was carried out on AE signals, AE cumulative event count, AE event count rate, frequency spectta of AE signals and crack length in the bending fatigue process of case-hardened or normalized spur gear teeth under different
tooth loads. The relationship between the AE parameters and the fatigue crack propagation as well as effects of thegear material and the tooth load on the AE characteristics in the fatigue process were determined. It was found thatthe peak amplitude of the AE signal and the peak level of the frequency spectra in the case of case-hardened gears aremuch larger than those of normalized gears. Basic data was obtained for the prediction and diagnosis of bending r.
tigue failure of the gear tooth by means of the AE method.

1. Introduction
With increasing demands for higher efficiency of production and quality level of products, monitoring techniques
for failure prediction and diagnosis of machinery of industrial plants are now a matter of great concern. The machinery has a large number of machine elements such as gears, rolling bearings and so on. It is therefore important todevelop techniques for failure prediction and diagnosis of gears and rolling bearings. So far, abnormalities of machineelements in service have been detected on the basis of vibration and noise. With this method of detection, however,abnormalities at an early stage cannot be detected and their diagnosis becomes possible only after the damage hasadvanced to a considerable extent

In the acoustic emission (AE) method, microscopic deformation and fracture of the material can be detected(Harris and Dunegan, 1974; Onoe et aI., 1976). In recent years, a technique for the condition monitoring by means ofAE has increasingly come into use, and there have been a number of reports pointing out that AE monitoring can beeffectively used for the diagnosis of abnormalities in the rolling bearing (Yoshioka and Fujiwara, 1989; Li andInasaki, )989). Examples of AE measured under running condition for the gear have been published (Kondo and
Takada, 1991), but the relationship between gear failure and AE has not yet been clarified.
In the present paper. acoustic emission in the bending fatigue process of spur gear teeth was investigated. Research was carried out for the prediction and diagnosis of bending fatigue failure of the gear tooth by means of the AE
method.

2. Experimental Procedure and Apparatus
Dimensions of test gears used in this experiment are shown in Table I together with their materials and working
and beat treatment conditions. Test gears G.A and G.B are case-hardened gears with different case depths (G.A: 0.9mm at Vickers hardness, Hv = 550, G.B: 1.8 mm). Test gear G.C is a normalized gear. Fig. I shows the hardness
distributions of G.A and G.B.
AE signals, AE cumulative event count, AE event count rate, frequency spectra of AE signals and crack length in thebending fatigue process of case-hardened gears G.A, G.B and the normalized gear G.C were recorded. Crack-length
measurements were made with a 400-power microscope. The suppon condition of the test gear and the posiReceived October 20, 1994. The authors are affiliated with Faculty of Engineering, Tottori University. 4-101, Minami,
Koyama-c:bo, Tottori, 680 Japan. Based on a paper that was given at the 12th International Acoustic Emission Symposium,
Sapporo, Japan and was included in the proceedings, Progress in Acoustic Emission VII, JSNDI, Tokyo. Japan.

Journal of Ac:oustic Emission
Volume 13. Numbers 1/2

S47

O'13()..()OSGl'SlSS.00I13S47-SS3
Copyright QI995ACODStic Emission Orovp

12th Intemational AE Symposium, Sapporo. Japan
Table I Tested gears
Gear sign

G.A

900 r-----,-----~--~

I G.B

G.C

Modulem

4

Pressure anglea20°

Number of teeth z
Face widthbMaterial

IS

Treatment
conditions
Case depth(at Hv = 550)

10 DIID
SCM415
BobbedCase-hardened
0.9 DUD

I.. s

:z:>
III
III

BOO - - - - - - - : : l o k - - - - t - - - - - lellc:~ 700 r----To-f--'\----f---~
.s::.
III

SUIID

~ 600 t----\o-+---~-t----~

~

u

S45C

;>

500 1--~--f"'::::::==1

HobbedNormarized

4000

DUD

loading bar

1
2
Distance from surface mm

3Fig. 1 Hardness dislributions of case-hardened gears.

Pressuretransducer(load value)

SpacerSpectrum analyzer

Bed

(B)

Fig. 2 Suppon condition of test gear and position of
AE sensor.

Fig. 3 Block diagram for AE measurement.

tion of an AE sensor are shown in Fig. 2. The sensor is coupled to the test gear with high vacuum silicon grease,and held in place with a holder adhered to the gear. A block diagram of AE measurement used in this experiment isshown in Fig. 3. The output signal from the AE sensor was amplified 40 dB with a preamplifier, and filtered arxI
amplified 30 dB before a discriminator. The number of event pulses for AE signals, whose peak amplitudes exceed athreshold level, were counted as AE cumulative event count as well as AE event count rate with the dual counter, andthese were recorded simultaneously by using a chan-recorder. The AE signal from the discriminator and the load
waveform amplified through a dynamic strain-meter from a pressure transducer were measured on the digital oscilloscope and recorded on the floppy disk of the micro-computer. A frequency analysis of AE signal was also carried out.

Figure 4 shows the bending fatigue testing machine used in this experiment. In order to reduce the extraneousbackground noise from contact impact between the loading bar and the tooth surface, the hydraulic loading cylinder ofthe conventional testing machine (Oda et aI., 1980) was improved as shown in the insert. This apparatus has two
cylinders; an upper cylinder for the cyclic load and a lower one for the constant load.
In order to find the AE characteristics in the fatigue process, the fatigue tests were carried out under an applied
load PIb =1.03 kN/mm (P = 1.14 Pu) for G.A and Pib =0.90 kN/mm (P ~ 1.27 Pu) for G.C corresponding to thefatigue life N = 10' as shown in Fig. 5 (Oda and Tsubokura, 1980; Oda et al.. 1989). For G.B, the fatigue test wasalso carried out under PIb = 0.95 kNlmm in order to examine the effect of Ihe tooth load on AE parameters. Here, Pu
corresponds to the load of bending fatigue limit. and b is the gear face width.

S48

12th International AE Symposium, Sapporo. Japan

11Il&.. ..+t--f Constant pressure
generator

CD PUlsating pressure generator CD Pressure controller

CD loading apparatus
Fig. 4 Bending fatigue testing machine with a detail of an improved hydraulic loading cylinder.

3. Experimental Results and Discussion
Figure 6 shows the AE signals and their frequency
spectra just after the beginning of the bending fatigue

1.2 ,......-----,.---,.-----....--....-----,~

test of G.A (at this stage, AE signals produced by the ~ ID~---~~:_f.....;:::........~-_+-_+--_t
fatigue failure cannot be observed). Figure 6(a) shows .s::J
the case under the cyclic load Pib = 1.03 leN/mm. The ~signal is originated by cyclic impact between the tooth
surface and the loading bar. and the peak amplitude islarger than 1.5 V and the frequency range 60-800 kHz.
Figure 6(b) shows the case under both the cyclic load 0
Pib 1.03 leN/mm and the constant load P/b = 0.01 ~ 0.61----+--r----+-~~----lleN/mm. As the impact is reduced by applying the conG.A} Case-hardened georstant load, the noise level can be reduced to about 0.5 V
G.B
and the level of the components of the frequency near
6.t : Normalized gear
0"10'
lOS
10'
200 kHz becomes lower. Figure 6(c) is obtained by fittering AE signals of Fig. 6(c) with the bandpass filter
Number of load cycll!s N
of 200-1000 kHz, considering the frequency range of AE
Fig. 5 S-N curves for test gears.
signals of fatigue failure. The noise level is found to be
reduced to about 0.25 V. On the basis of these results.
the subsequent AE measurements were carried out under the condition given in Fig. 6(c).

=Figure 7 shows the AE cumulative event count. the AE event count rate and the crack length in the bending fatigue process. In this figure, the marked increases in the AE cumulative event count and the AE event count rate forboth G.A and G.B can be observed just before the crack initiation. but not those' for G.C. This'might be because in~ gears. the peak amplitude of AE wavefonn just before the crack initiation is much higher than thenoise level but in normalized gears the noise level is almost the same. Therefore. the prediction of crack initiation bymeans of the AE method is possible for case-hardened gears but it is difficult for normalized gears.
Figure 8 shows the AE cumulative event count. the AE event count rate and the crack length in the fatigue
process of G.B for Pib = 0.95 leN/mm. These AE parameters show the same tendency as the case of G.B for Pib =1.03 leN/mm (cf. Fig. 7(b». The number of cycles to the marked increase of AE cumulative event count becomeslarger with decreasing tooth load. Figure 9 shows simultaneous traces of load and AE intensity during crack growthof G.A. It is seen from this figure that the AE is generated just before the maximum load. Figure 100a) shows theAE waveform near the peak load in Fig. 9. while Fig. 1O(b) shows the AE waveform from the fatigue failure of12th International AE Symposium. Sapporo, Japan
6,A

PIlI.I.oJ kIIJlMl

UICcst-IlardInIdI>

t~·OU!r.110

UlhlS

-I

'2

-2

100

i 75
:a

in

~.QOlk./I:IIlEl

6ail:70 clII
8Pf:lllII-llIXI kill

in
!

.

1~

SI

P/lI.I.o:J1lMMl

6.A>

P.JlI.QOltlll_&aift:70 dlI

'Ii

8'
~

lillll100'~.I.o:Jtll/lllm

G.A

6aln:~d8

1.§D

Iillll100i"6ail:70 dB
8Pf:lllII-llDl1dl1

j·1

PflI.l.l13 tlVlND
tfll.Okll/lllm&AP~.I.ll3kllJllltll~.QOltllll!llll

0

limt

100

6.A

>

i

~
'2

,~ .I.oJ kNllMl
P.~ .001 tlllmm&a:n:70 llll

I,6o;n:70 d8

~

5lI

SI

25

o

200

40ll

600

III

f rtqIIIIlCJ kill

o

1000

fiOO
III
frequtrqkHr(c) PIb = 1.03 kN/mm,
PJb=O.Ol kNlmm,
BPF:2OD-1000 kHz(b) PIb=l.03 kN/mm,(a) PIb=l.03 kNlmm,

PJb=O.Ol kNlmm

Pr/b=O kN/mml(OlFig. 6 AE signals and frequency spectta.

...

u

6.A

~
......
u

115
~
l;

~IO

4

I

.102

P.IOJkH&oIn:70 dB
BPF:200-IOOO kHz
v.' 250 mV
V.' 500 rrN

..

<II]

c
c

'"
82

i
1
...

5
Crack lengl~"

j

•

I

I 1•
,

AE event counl role

~ 5 ~I

2 ....
EN,Y:

AE tumullllive l!Yl!IIl counl~

is

coun~

2
4
6
Number of ICIlId cycles N

B'lO'

Crock
length..

(a)

I

~

(-

tI
3

5

UOillmlllIiZedl

PIb.ll!II kIlImm
6oIn:70 dB
BPf:200-llIOIJ kHz
V.' 150 mV
V.' 300 mY
AE cumulolive
AE ~ count rote

71I
'

counl

e

.&;

~
.;;t;

!
:

o

' II

,

I

.-!.

,

4
6
B
IIumller 01 tDOd cycles N

2e
1~

I

.'
2

1

I

Cratk lenglh

G.Blease-hardened)
P/b =1.03 kN/mm
6ain:70 dB
BPF:200-1000 kHz
VL =250 mV
VH =500 mY

o

I

o

AE cumulative
event count V
AEevent LJ

10

o
.,0'

~

e

u

00
1
2
3
'~10'
Number of load cycles N
(b)

(e)

Fig. 7 AE cumulative event count, AE event count rate and crack length in bending fatigue process.
(a) G.A. (b) G.B. (e) G.e

SliD

12lh Inlemational AE Symposium, Sapporo, JapanI

U
6.B ICase-hardened) I
P/b:O.95 kN/mm AE cumulative
event counU
Gain:70 dB
BPF:200-1000 kHz
VL : 250 mV
VH : 500 mV

u

gS

...

G.A (Case-hardened)

z:

>

'J

8

IS

DB

10 a..

II>
Cl

~

EO'

'0
>

5

0

0

3

2

2

J

I I

~

,,

·0.'

Goin:70 dB

..c

2 0.
c
..2!

-IS

·08
Time

u

0
<-

,\

}I,

Fig. 9 AE and load wavefonns.

C-)

'w~

~

III

Z
3
4
5
6
Number of lood cycles N-10

BPF:z00-I000 kHz.:.:

Crock 'length

o

-5

e
e

I

AE event count rate

.§

o

7·10'

Fig. 8 AE cumulative event count, AE event count rateand crack length in bending fatigue process (G.B: P/b
0.95 kN/mm).

=

z

Z

P/b: 1.03 kN/mm
Gain:70 dB
BPF: 200-1000 kHz

>

&

>

'"
~I
~

E

~

0

---

G,( lKarmalized)

PIb: O.SO kN/mm
Gain:70 dB
BPF:ZOO·1000 kHz

0

-1

-I

G.AlCose-hardened)
-Z

-2
lime

Hme

Fig. lO(a) AE waveforms; G.A.

Fig. lO(b) AE wavefonns; G.C.

G.C. It can be seen from these figures that the peak amplitude of AE wavefonn of G.A is much larger than that of
G.C. Figure II shows the frequency spectra of AE signals in the fatigue processes of the gears. The peaks of frequency spectra in the case of case-hardened gears occur at 200, 500 and 800 kHz, and the marked increase of thesepeak levels can be observed just before the crack initiation as well as for the AE cumulative event count and for the
AE event count rate (Fig. 7(a), (b)J. The fatigue crack occurs earlier for G.B than for G.A and the peak level of frequency spectra is larger for G.A than for G.B. The time period of occurrence of the spectra with high peak levels
corresponds to that of the marked increase of the AE cumulative event count [Fig. 7(a), (b)), and is longer in G.A
than in G.B. At an earlier stage in the fatigue process, spectra with high peak levels occur. These spectra will befurther investigated by examining the change of the micro~tructure in the fatigue process. It can be seen from Fig.
Il(c) that the peaks offrequency spectra for normalized gears (G.C) occur at 300 and 500 kHz and the variation of thepeak level in the fatigue process is considerably smaller than for case-hardened gears.

551

12th International AE Symposium. Sapporo. Japan(i) N=7.2 X 10 4

G.Altose-hordenfil)
P/b :1.03 kll/mm

Goin:70 dB
BPF: 200· 1000 kHz
... U

'---'

2

:g C '10~HOrdened loyer

0.2 mm~5610~.'::kll,:750 k5~O
~ 0
0.5
I

200

<{

>
E

,

2

"'silion 01 crock tip mm...... 150~(ii) N=7.5 X 10 4

glOO(a) G.A (PIb=I.03 kN/mm)%

p-~ -,~

50

o

,
15

200

400

600 800 1000 0
Frequency kHz--.......-"'!""(i) N=2.1 X 10 4(a) G.A
G.B ((ose-hordel12d1
P/b =1.03 kNlrnm

liain:70 dB

BPF:200'IOOO kHz

150

o

05

I

15

2

Position 01 crock tip mm(ii) N=2.4 X 10 4(b) G.B (PIb=I.03 kN/mm)o(b) G.B
G.e (Normalized)
Pib =ago kH/mm

6oin:70 dB

BPF:200'11100 kHz~

0,1 mm(i) N=6.0 X 10
>100
E

...

:a 50
£
o

,-

4

(ii) N=8.0 X 10 4---.,.,'/ 3.~.- .... ...

_" , ;

200

400

600 800 11m 0Frequency kHz(c) G.eFig. II Frequency spectra of AE signals.

(iii) N=9.0 X 10 4'--'

0.2 mm(c) G.e (PIb=O.90 kNlmm)
Fig. 12 Photograph of fatigue cracks.

Figure J2 shows a photograph of fatigue crack of the tested gears. The relationship between AE cumulative
event counts. the position of the crack tip and the hardness of the hardened layer shown in Fig. I are also shown. It
can be seen from Figs. 12(a) and (b) that AE cumulative event counts of both G.A and G.B markedly increase with

12th Intemational AE Symposium, Sapporo, Japan

crack growth when the crack grows from the surface up 10 the position of hardness Hv = 750, but becomes almost
constant when the crack grows still funher. From Fig. 12(c) the plastic deformation along the crack for the nonnalized gear is found to be much larger than that for the case-hardened gear.

4. Conclusions
The main results obtained from this investigation can be summarized as follows.
(I) The peak amplitude of AE wavefonn of bending fatigue failure of case-hardened gears is much larger than that ofnormalized gears.
(2) Marked increases of AE cumulative event count and AE event count rate in the bending fatigue process of gear
teeth can be observed in the case ofcase-hardened gears but not in the case of normalized gears. Hence, the predictionof the crack initiation by means of the AE method is possible in the case of case-hardened gears, but it is difficult in
the case of nonnalized gears.
(3) The AE cumulative event count of the case-hardened gear markedly increases with crack growth when the crack
grows from the surface up to the position of hardness Hv = 750, but becomes almost constant when the crack grows
still further.
(4) The peaks of frequency specb'a of AE waveform in the bending fatigue process occur near 200, 500 and 800 IcHz
in the case of case-hardened gears, and near 300 and 500 kHz in the case of normalized gears. The marked increase of
the peak level in the bending fatigue process of case-hardened gears can be observed just before the crack initiation,
but the variation of the peak level for normalized gears is considerably smaller than for case-hardened gears.

Acknowledgment
The authors wish to thank Mr. C. Namba of the Deparunent of Mechanical Engineering of Tottori University
for his assistance in canying out this investigation.

References
D.O. Hams and H.L. Dunegan (1974), "Continuous Monitoring of Fatigue-aack Growth by Acoustic Emission
Techniques", Experimental Mechanics, 14, 71-81.
K. Kondo and J. Takada (1991), "Diagnosis of Gears by Acoustic Emission", Int. Conf on Motion and Power
Transmis., p. 763.

x. Li and I. Inasald (1989), "Monitoring of Rolling Element Bearing by Using An AE Sensor", Tribologist, J. JST,34(4), 278-282.
S. Oda. T. Sayama and Y. Shimatomi (1980), "Study on Welded SlrUeture Gears (1st Report, Effect of Rim Thickness on Root Stresses and Bending Fatigue Strength)", Bull. JSMB, 23(175), 132-139.
S. Ods and K. Tsubokura (1980), "Bending Fatigue Strength of Spur Gears in Vacuum", Bull. JSME, 23(181),
1228-1234.
S. Oda. K. Tsubokura and T. Koide (1989), "Impact and Bending Fatigue Strength of Case-Hardened Gears at Low
Temperature", Trans. Jpn. Soc. Mech. Eng., 55(518), 2587-2590.
M. Onoe et al. (1976), "Basics and Application of Acoustic Emission", Corona-sha, Tokyo.
T. Yoshioka and T. Fujiwara (1989), "Acoustic Emission and Vibration in the Process of Rolling Contact Fatigue(1st Report)", Tribologist, J. JST, 34(1), 36-42.

12th International AE Symposium, Sapporo, Japan

Characterization of Thermal Cracking by Acoustic
Emission Time Series Analysis
Koji Nagano, Katsuhiro Sugawara, Ken-Ichi Itakura and Kazuhiko Sato
Abstract
Acoustic emission (AE) time series measured during thennal fracturing in granite were divided by a time-shifted
window and investigated by spectral analysis. Below the threshold temperature. above which AE events suddenly
increased. AE time series had a flat power spectrum indicating that AE events had little correlation with each other.
Above this threshold temperature, power spectral densities had power spectra which increased inversely to frequency;
i.e., a lIf power spectnDn. Crack extension was visible on the sample surfaces when AE activity increased. Twocrack extension patterns were observed; i.e.. either parallel or perpendicular to the rift plane. Parallel cracks werelarger than perpendicular cracks. AE time series with IIf power spectra were observed more frequently when the crack
was parallel to rift plane. These results indicate that the shift from fiat power spectra to IIf power spectra reflects
large scale crack extension during thennal cracking.

1. Introduc:tion
Thermal microcracks in rock masses have attracted considerable attention in the field of nuclear waste storage.
Thermally induced microcracks form pathways. into which radioactive-contaminated water can permeate. In hot dry
rock geothermal energy production. water is injected into hot intact rock to produce a permeable fracture which serves
as a heat exchanger. However. cooling induced by the injected water may lead to thermal cracking. Therefore. it isimportant to study the fracture mechanism of thermally induced cracks.
Analysis of time intervals of the onset of AE event is one method for examining a dynamic fracturing process.
Hirata (1987) measured AE time intervals in a mechanical loading test using Murata basalt. He showed that AE sequences after the main shock could be characterized as either exponential decay type or Omori's power law type. As
the fracture process progressed. AE time intervals changed from exponential decay type to Omori's power law type.
Nagano et at (1993) studied intervals measured during a hydraulic fracturing experiment at a geothermal field.
They reported that the process of subsurface fracture extension could be divided into three stages based on the resultsof AE interval analysis. However. they did not discussed the mechanism of hydraulic fracturing.
In this paper. we describe the results of our statistical analysis of time intervals in thermally induced AE eventsin granite. We conducted a thermal fracturing experiment in granite and measured AE time intervals. This experiment
was planed to study the phenomenon of thermally induced fracturing and to devise its characterization method. Statistical characteristics of the AE time intervals were studied by spectral analysis. Changes in the power spectra are discussed as they relate to crack extension behavior.

2. Experimental Method
The rock sample consisted of a 0.20 m cube of Fujian granite. Such a large sample should be useful for recognizing the difference between AE events during microcrack extension and those during ultimate fracturing. This
granite has a uniform composition with an average grain size of about 3 to S mm. Compressional wave velocities
parallel and perpendicular to the rift plane before heating are 4430 mls and 4344 mls. respectively.
Received October 20, 1994. The authors are affiliated with Department of Computer Science and Systems Engineering.
Muroran Instirute of Technology. Mizumoto 27-1. Muroran 050, Japan (nagano@yama.csse.muroran-it.ac.jp). Based on apaper that was given at the 12th International Acoustic Emission Symposium. Sapporo, Japan and was included in the proceedings. Progress in Acoustic Emission VII. JSNDI. Tokyo, Japan.

Journal of Acoustic Emission
Volume 13. NumbeJs 1/2

0730-00SOI9SJSS.00I13SS4-SS9

Copyright el99SAcoustic Emission Group

12th Intemational AE Symposium, sapporo, Japan

AE Sensor
Thermocouple

AE Sensor
Sando

Cartridge
Heater

Thermocouple
Sand---+t.Ji-----1- Cartridge
HeaterFujian Granite
Fujian Granite

FAONTVIEW

PLAN VIEW

~

100mm

.

Fig. 1 The experimental system for the AE measurement and the thermal fracturing.

3000

3000

200

J!l
c

iii'

!!
c

~2000
<

~
:g.

0

e

~

200
'iii
G)

...

~

0

Cl
G)

w 2000

:Eo
G)

... <
GI

"'C

100 ~

J!
as

'3

CD
0.

e

§ 1000

~

~

O 0

100

0

-

100 ~
...

"CJ

G)

.!!!

CD

::J

Co

§1000

E

~

t-

u

C1l

('
0 0

100

Tune(mln)

Time(min)00~

Fig. 2. Accumulated AE counts and temperature in the thermal fracturing. A borehole is (a) parallel and (b) perpendicular to the rift plane.
A borehole (20 rom in diameter and 100 mm depth) was drilled at the center of the top plane. Two separate experiments were performed; i.e.• the hole was bored either parallel or perpendicular to the rift plane. Figure I shows asetup of the experiment. A 250 W cartridge heater and a thermocouple were installed in the borehole. The thermocouple was employed for feedback temperature conuol by a programmable temperature controller. The borehole wasfilled with sand for thermal coupling. The average heating rate was about 1.7 °Clmin and the maximum temperature
was 220 °C. We used a high heating rate at the beginning of the experiment so that a macroscopic crack could extend
more clearly.
AE events were monitored during the experiments. An AE sensor was affixed with grease 80 mm from the borehole on the top plane. 1bis AE sensor can detect frequency components from 100kHz to 1 MHz. An AE sequence
detector determined that a signal was an AI:. event and identified its onset. Intervals between AE event detection times
were measured by a counter having the -time resolution of 10 ms. With this time-interval measurement system. wecannot measure the exact time interval if it is less than the resolution. or if the duration of the AE event is greaterthan the resolution. or both. However. in a preliminary experiment we detennined that the number of such AE
events was very small. Therefore. this error should have no appreciable effect on the results.

12th International AE Symposium. Sapporo. Japan

3. Acoustic Emission

Accumulated AE counts and temperature under the two heater-setups are plotted against time in Fig. 2. Low AE
activity was observed below J90 0c. observed Above this threshold temperature, AE event rate increased sharply.
This pattern of AE activity was detected regardless of whether the borehole was parallel or perpendicular to the riftplane. A sudden increase in the number of AE events above a threshold temperature has also been reponed by Wang
et aI. (1989).
When the number of AE events increased rapidly at 190°C. a visible crack appeared on the top and side surfaces
in both of the experiments. These visible cracks extended almost parallel to the borehole axis. Therefore, we examined two crack-extension patterns: parallel and perpendicular to the rift plane. When the crack was perpendicular to
the rift plane. AE activity increased rapidly at the threshold temperature and declined thereafter. On the other hand.
when the crack was parallel to the rift plane. AE activity increased gradually and no clear critical temperature wasobserved.

4. Acoustic Emission Time Intervals
We performed a statistical analysis of AE time intervals. Figure 3 shows typical AE sequences. with AE event
detection times represented by an impulse series. Bursts of AE events were observed throughout the experiment. A
burst could be chaJacterized in terms of the duration and number of AE events. Furthermore. several small-scale
bursts could often be found within large-scale bursts in some AE sequences. as shown in Fig. 3(d). The AE timeseries was divided into subsets using a time-shifted window. We examined the statistical properties of the AE timeintervals in each subset so that we could investigate relations between the statistical properties and crack extension
process. The length of the window is shown in Table I. When the number of AE events was small. a statisticalanalysis of the intervals could not be performed. Therefore, the length of the window for data obtained below thethreshold temperature was greater than the length of the window above the threshold temperature. and subsets. inwhich the number of AE events was less than 20. were excluded from the analysis.
Power spectra of the impulse series in Fig. 3 are shown in Fig. 4. Statistical properties of the AE time intervals
can be expressed in a frequency range less than the reciprocal of the average number of intervals in power spectrum
analysis (Kobayashi and Musha, 1982). The maximum frequencies which can be examined in the power spectrum
analysis of intervals are 0.03 Hz to 1.3 Hz. At low frequencies. impulse series generally have sloping power spectra.
As shown in Figs. 4(a) and (b). some subsets show flat power spectra, while other power spectra vary inversely withfrequency, as shown in Figs. 4(c) and (d).
Low frequency components of a power spectrum S(f) can be expressed approximately by S(f) oc I D where f isfrequency and n is a power law index. Figure 5 shows the power law index n in each subset as it relates to temperature. Before the threshold temperature was reached, n was close to zero. When the temperature exceeded the threshold,the number of spectra with a high n was much greater than that before the threshold temperature was reached.
Table I Length of the subsets in the AE time interval analysis.
Crack Extension Patterns
Perpendicular to the rift plane:
Below the threshold temperature
Above the threshold temperature
Parallel to the rift plane:
Below the threshold temperature
Above the threshold temperature

Time (min: s)Length of Window (s)0:0.0
82:57.52

83:39.9
116:47.56

1310.72
163.84

0:0.0
81:51.51

74:35.65
116:47.56

13)0.72
163.8412th International AE Symposium. Sapporo. Japan
Itnber or "' eYenls 34/Ulller or j:E _nts 33

.....

....
T I " E

6 (So'divl

T I" E(a)

S '-ivl(b)
ItAller or j:E _nts

IUlb8r or j:E _n1s 'Ie

4l!I

.

w

T I "E

S (lYdivl

B
94:31.0

93:51.16

TIn E

S llYlIivl:12. 41(d)(c)

Fig. 3 Typical AE time series. These data were obtained during the experiment shown in Fig. 2(b).
~rSpectrum

PrAax = 133.ASl113

Power Spectrum

Pmax .. 119.S99838

13

.

..
Cl

D

:r

:I

o

o

CI.

CI.

-40

-m10"'k--~2----;:n'ib:-r--;-1 ---"lB"9~----;:n~rl---b-mUI-b:2----;J~lr=---;I,..---......-;leb;"0;;-----:l:o;;ilr=-J.---l

Frequency (Hz]Tlt£ : 85:2.4J-85:43.31

Frequencv 1Hz)
TUE : 88: 47.29-s9:28.25

(a)

(b)

PnBx ~ 558.382812

B

..
Cl

Cl

:r
o

:r
o

CI.

CI.

-413

~eA~-"=2---""10~A::--""I---~u=re---·Jlr=J--~~0"'!:--~2-----,J;;;lr=---;1---"ii1n~---'iiJlr~I--c!50
Fr8(lUencv (Hz)Frequencv 1Hz)
Tlt£ : 94:3).45--95:\2.4J~

MTlt£ : 93:1e.22~:51.18

Fig. 4 Power spectral densities of the AE time series. These power spectra are the Fourier uanfonn of the impulse
series in Fig. 3.

S57

12th Intemational AE Symposium, Sapporo. Japan

1000
II)

II)

c::J

C

<.>

()

3000

::J

0

0

w

w

«
"0
co

0

Q)

0

0
0

"3

2000
«
"0
•
co

c:

Q)

0

"3

E

0

o c:

0

•

0

0

E

;:]

;:]

«

«

u
u

u
u

0

100

0

1000

0 LJ....-==:c::::;::::;:::::::::;::::::......----..........--.J_l
0
100

-1

TIme(min)Time(min)W

M

Fig.5 A power law index n which characterizes the power spectrum of the AE detection time. Low frequency components of the AE time series are expressed by S(n oc rD. (a) Crack extension perpendicular to the rift plane. (b)Crack extension parallel to the rift plane.
Moreover. when the cracks extended in different directions, the AE time intervals showed different properties.
When the crack was parallel to the rift plane. AE data with a high n was observed over a long period. On the otherhand. for crack extension perpendicular to the rift plane. data with a high n were observed only at the threshold temperature when there was a sudden increase in the number of AE events. The ratio of AE events with a high n in parallel crack extension was higher than that in perpendicular crack extension.

5. Discussion
Before the threshold temperature was reached, we observed flat power spectra at low frequencies. A flat power
spectrum indicates that the AE events occurred independently of each other (Musha et aI.• 1985). Jansen et aI. (1993)
studied AE souree distribution in a thennaIly induced crack. Before the threshold temperature was reached. AE sourceswere scattered throughout the sample. At this time, they reponed that a macroscopic crack had not yet developed. The
independence of AE detection times that we observed appears to be closely related to the scattered AE sources in Jansen's experiment. Therefore, a flat power spectrum reflects microcrack extension in a large sphere prior to ultimate
fracturing.
After the threshold temperature was reached. a power spectrum which increased inversely to the frequency. i.e.,
lift was characteristic. Such Jlf power spectra were observed concurrently during both visible crack extension and in
the sudden increase in AE events. Moreover, crack extension parallel to the rift plane showed AE time series with lIf
power spectra more often than perpendicular extension. Therefore, the lIf power spectrum in AE sequences may be acharacteristic feature of macroscopic fracturing.
The flat and the Jlf power spectra are identical to the exponential decay type"and Omori's power law type. respectively. in a frequency analysis of AE events between t and t + dt (where t is measured from the origin of the main
shock). Hirata (1987) reported that when the fracture process progressed during the compressional fracturing of basalt.
AE sequences after the main shocks changed from exponential decay type to Omori's power law type. Therefore, ourresults with the thermally induced cracks were identical to those in Hirata's compressional fracturing.

Although we obtained the same results as Hirata (1987), we did not classify AE events into main shocks and aftershocks. Such a classification. which is determined by the researcher. can detract from objectivity. The difficulty inclassifying AE events can be overcome when the AE time interval analysis is carried out in a real-time estimation of
dynamic fracture extension.

S5B

12th International AE Symposium, Sapporo, Japan

6. Conclusion
We have described time intervals of thermally induced AE in granite. Below the threshold temperature. the AE
time series showed flat power spectra. This implies that the AE events occur independently of each other. Above thethreshold temperature, the power spectral densities of AE time varied primarily as 1If. We observed visible crack
initiation and profuse AE events at the same time we detected AE time intervals with IIf power spectra. This change
from flat power spectra to llC power spectra in AE time series may reflect macroscopic crack extension in thermallyinduced fracturing.
References
T. Hirata (1987), "Omori's Power Law Aftershock Sequences of Microfracturing in Rock Fracture Experiment", J.
Geophys. Res., 92, 6215-6221.
D.P. Jansen, S.R. Carlson, R.P. Young and D.A. Hutchins (1993), "Ultrasonic Imaging and Acoustic Emission
Monitoring of Thermally Induced Microcracks in Lac du Bonnet Granite", J. Geophys. Res., 98, 22231-22243.
M. Kobayashi and T. Musha (1982), "lIf Fluctuations of Heartbeat Period", IEEE Trans. Biomed. Eng., BME-29,
456-457.
T. Mush&. K. Katsurai, and Y. Teramachi (1985), "Fluctuations of Human Tapping Intervals", IEEE Trans. Biomed.
Eng., BME-32, 578-582.
K. Nagano, M. Aida. K. Sato, H. Niitsuma and H. Kaieda (1993), "Acoustic Emission Sequences Measured in
Ogachi HDR Geothermal Field", Proc. 1993 International Symposium on Nonlinear Theory and its Applications,
Honolulu, vol. 3, pp. 863-866.

H.F. Wang, B.P. Bonner, S.R. Carlson, B.J. Kowallis and H.C. Heard (1989), ''ThennaiStress CrackinginGranite",J. Geophys. Res., 94, 1745-1758.

AVAILABLE BOOKS ON ACOUSTIC EMISSION
Progress in Acoustic Emission VI (1992) The Proceedings of the 11th International AE Symposium.
This volume is $ 150 plus shipping. Earlier Proceedings volumes also available. Inquire below.
Progress in Acoustic Emission VII (1994) The Proceedings of the 12th International AE Symposium.
Cost of this volume is -$ 200 and should be ordered directly to JSNDI. Tokyo.
Proc. Second International Conference on AE (1985) October 1985. about 350 pages $ 50
Proc. World Meeting on AE (1989) March 1989. about 350 pages $ 50
Acoustic Emission· A Bibliography with Abstracts (J979) T.F. Drouillard 806 pages. Published by
Plenum Press. $ 135 post paid (surface).
Fundamentals of Acoustic Emission (1979) Ed. K. Ono - microfiche version only 360 pages. $ 10.
Journal of Acoustic Emission, Vol. 1 • 3 (1982 - 84)$ 50 per volume (plus shipping)
Journal of Acoustic Emission, Vol. 4 • 8 (1985 - 89)$ 90 per volume (plus shipping)
Journal of Acoustic Emission, Vol. 9 • 12 (1990. 91192. 93. 94) $ 96 per volume (plus shipping)
Above are available fromAcoustic Emission Group308 Westwood Blvd, Box 364
Los Angeles, CA 90024·1647
FAX 1·818·368·8309

NDT HANDBOOK (2nd Edition), Vol. S, Acoustic Emission Testing (1988)
Eds. R.K. Miller and P. McIntire. 650 pages. $110.25
Third International Symposium on AE from Composite Materials (1989) Cat. No. 770.
Fourth International Symposium on AE from Composite Materials (1992) Cat. No. 1335.
Proc. Fourth World Meeting on AE (1991) Sep. 1991. Cat. No. 1332.
Advances in Acoustic Emission (1981) eds. Dunegan & Hartman 385 pages - $ 68.
Available from Book Dept., ASNT. P.O.Box 28518. Columbus. OH 43228. Also call (800) 222-2768.
First International Symposium on AE from Reinforced Plastics (1983)
Proceedings of the San Francisco Symposium. July 1983. about 400 pages - $ 50 + shipping.
Second International Symposium on AE from Reinforced Plastics (1986)
Proceedings of the Montreal Symposium, July 1986. about 225 pages - $ 65 + shipping.
A vailable from Publication Sales. SPIt 355 Lexington Ave.• New York. NY.
Acoustic Emission (1983) J.R. Mathews 167 pages.
Basic Acoustic Emission (1991) Ian G. Scott. 246 pages. Available from Gordon & Breach. New York.
Third Conf. on AEIMicroseismic Activity in Geologic Structures and Materials (1982)
Fourth Conf. on AEIMicroseismic Activity ia Geologic Structures and Materials (1989)
Fifth Conf. on AElMicroseismic Activity in Geologic Structures and Materials (1991)
Eds. Hardy & Leighton. Available from Trans Tech Publications. 16 Bearskin Neck. MA 01966.
Acoustic Emission (1980) tr. A.R. Nicoll 385 pages - $ 63.
Available from DGM Metallurgy Information. 150 E. 27th St.. New York. NY 10016
Acoustic Emission (1980) R.V. Wi1lia~s 140 pages - $ 29.
Available from A. Hilger Ltd. Bristol. UK or Heyden & Sons. Philadelphia.
ASTM·STP's: Acoustic Emission (1972). STP-505.
Monitoring Structural Integrity by Acoustic Emission (1975), STP-57I.
Acoustic: Emission Monitoring of Pressurized Systems (1979). STP-697.
Acoustic Emission in Geotechnical Engiaeering Practice (1982). STP-7S0.
Acoustic Emission, Current Practices and Future Directions (1991). STP-I077.
Acoustic Emission Testing of Aerial Devices and Associated Equipment used in the
Utility Industries (1992). STP-1I39. Available from ASTM. 1916 Race St. Philadelphia, PA 19103.
S60

Notes for Contributors
1. General
The Journal will publish contributions from all parts of theworld and manuscripts for publication should be submitted
to the Editor. Send to:Professor Kanji Ono. Editor - JAE
6531 Boelter Hall, MSE Dept.
Dnivers ity of California
Los Angeles, California 90095-1595 USA
FAX (I) 818-368-8309
e-mail: ono@seas.ucla.edu
Authors of any AE related publications are encouraged tosend a copy for inclusion in the AE Literature section to:
Mr. T.F. Drouillard, Associate Editor - JAE
11791 Spruce Canyon Circle
Golden, Colorado 80403 USA
All the manuscripts will be reviewed upon submission to
the Editor. Only papers not previously published will be
accepted. Authors must agree to transfer the copyright to
the Journal and not to publish elsewhere, the same paper
submitted to and accepted by the Journal.

References to published literature should be quoted in the
text citing authors and the year of publication. These are to
be grouped together at the end of the paper in alphabeticaland chronological order. Journal references should bearranged as below. Titles for journal or book articles arehelpful for readers, but may be omitted.
H.L. Dunegan. D.O. Harris and C.A. Tatro (1968), Eng.
Fract. Mech., I, 105-122.
Y. Krampfner, A. Kawamoto, K. Ono and A.T. Green(1975), "Acoustic Emission Characteristics of Cu Alloys
under Low-Cycle Fatigue Conditions," NASA CR-134766,
University of California, Los Angeles and Acoustic Emission Tech. Corp., Sacramento, April.
A.E. Lord, Jr. (1975), Physical Acoustics: Principles andMethods, vol. II, eds. W. P. Mason and R. N. Thurston,Academic Press, New York, pp. 289-353.
Abbreviations of journal titles should follow those used in
the ASM Metals Abstracts. In every case, authors' initials,
appropriate volume and page numbers should be included.
The title of the cited journal reference is optional.

A paper is acceptable if it is a revision of a governmental ororganizational report, or if it is based on a paper publishedwith limited distribution.

Illustrations and tables should be planned to fit a single
column width (87 mm or 3.3") or a double width (178 mm
or 7"). For the reviewing processes, these need not be ofhigh quality. but submit glossy prints or equivalent with thefinal manuscript. Lines and letters should be legible.

An abstract of about 200 words is needed for Research andApplications articles, while it should be shorter than 100
words for other articles.

4. Review

The language of the Journal is English. All papers should
be written concisely and clearly.
2. Page Charges
No page charge is levied. Fifty copies of off-prints will be
supplied to the authors free of charge.
3. Manuscript for Review
Manuscripts for review need only to be typed legibly;
preferably, double-spaced on only one side of the page withwide margins and submitted in duplicate.
The title should be brief. Except for short communications,descriptive heading should be used to divide the paper into
its component parts. Use the International System of Units(SI).

All manuscripts will be judged by qualified reviewer(s).
Each paper is reviewed by one of the editors and may besent for review by members of the Editorial Board. The
Board member may seek another independent review. In
case of disputes, the author may request other reviewers.
5. Electronic MediaIn order to minimize typographical error, the authors areencouraged to submit a floppy disk copy of the text. We
can read Macintosh and IBM PC formats. Those who canconnect to INTERNET can send the text portion to"ono@seas.ucla.edu". This will greatly shorten the time ofcommunication.
6. Color PhotographWe can print color photographs needed to enhance thetechnical content of an article. Because of the cost, theauthor is asked to pay $350 per page.

Contents
Pages 1-10
Pages 11·22
Pages 23-29
Pages 31-41

Pages 501-07
Pages 508-13
Pages 514-20
Pages 521-28

Pages 529-34
Pages 535·41
Pages 542-46

Pages 547-53
Pages 554-59

Page 30
Pages 42-44
Page 44
Page S60
Page 507

Early Detection of Damages in Journal Bearings by Acoustic Emission Monitoring
Dong-Jin Yoon. Oh-Yang Kwon. Min-Hwa Chung and Kyung-Woong Kim
Clustering Methodology for the Evaluation of Acoustic Emission from Composites
A. A. Anastassopoulos and T. P. Philippidis
Investigmion of AE Signals Emitted from 3n SiOx Layer Deposited on a PET Film
Masa-aki Yan3k3. Noritaka Nakaso. Yusuke Tsukaharn and Nelson N. Hsu
On Characterization and Location of Acoustic Emission Sources in Real Size Composite
Structures - A Wavefonn Study M. A. Hamst3d and K. S. Downs

Conrerences and Symposia
12th Internalional Acoustic Emission Symposium
A Wavefonn Investigation of the Acoustic Emission Generated during the Defonnation andCracking of 7075 Aluminum Steve H. Carpenter and Michael R. Gonnan
Acoustic Emission and Damage Evolution in 3n SiC Fiber Reinforced Ti Alloy Composite
K. Takashima. H. Tonda and P. Bowen
Cracking Process Evaluation in Reinforced Concrete by Moment Tensor Analysis of Acoustic
Emission
Shigenori Yuyama. Takahisa Okamoto. Mitsuhiro Shigeishi and Masayasu Ohtsu
The Interaction between Pore Fluid Pressure Changes and Crack Damage Evolution in Rocksand Subsurface Rock Structures Modeled froTll Acoustic Emission Data Peler Sammonds.
Philip Mcredith, Javier Gomez and Ian Main
Acoustic Emission Analysis ofTiAllnlcrmelallics Manabu Enoki and Tcruo Kishi
Recent Applications of Acoustic Emission Tesling for Plant Equipment
Masashi Amaya
Effects of Soil Acidity on Acoustic Emission Properties of Sugi (CryplOrneria Japonica)
Seedling
Keiichi Salo, Atsushi Uchiyama. Takeshi lzuta, Makolo Miwa. Naoaki Watanabe.
Takllfumi Kubo and Masami Fushitani
Acoustic Emission of Bending Fatigue Process of Spur Gear Teeth
Kouilsu Miyachika, Saloshi Oda and Takao Koide
Characterization of Themlal Cracking by Acoustic Emission Time Series Analysis
Kqji Nagano, Kalsuhiro Sugawam. Ken-lchi Itakura an:! Kazuhiko Sato
Future Meetings on Acoustic Emission
Historic Files (AEWG Meetings. AEWG Awards)
Call for papers
Available Books on Acoustic Emission
Cover Photogrnph

T.F. Drouillard

The Fifth International Symposium on Acoustic Emission from Composite
Materials at Sundsvall, Sweden

JOURNAL OF ACOUSTIC EMISSION
Editor: Kanji Ono
Associate Editors: A. G. Beattie, T. F. Drouillard, F. C. Beall and M. Ohtsu
1.

Alms and Scope of the Journal

Journal of Acoustic Emission is an international journal
designed to be of broad interest and use to both researcher andpractitioner of acoustic emission. It will publish original contributions of all aspects of research and significant engineering
advances in the sciences and applications of acoustic emission.
The journal will also publish reviews. the abstracts of papers
presented at meetings. technical notes. communications and summaries of reports. Current news of interest to the acoustic emission communities. announcements of future conferences andworking group meetings and new products will also be included.
Journal of Acoustic Emission includes the following classesof subject matters;
A. Research Articles: Manuscripts should represent completed original work embodying the results of extensive investi·
gation. These will be judged for scientific and technical merit.
B. Applications: Articles must present significant advancesin the engineering applications of acoustic emission. Material
will be subject to reviews for adequate description of procedures.
substantial database and objective interpretation.
C. Technical Notes and Communications: These allow publications of short items of current interest. new or improved experimental techniques and procedures. discussion of published articles
and relevant applications.
D. AE Literature section will collect the titles and abstractsof papers published elsewhere and those presented at meetingsand conferences. Reports and programs of conferences andsymposia will also be presented.
Reviews. Tutorial Articles and Special Contributions willaddress the subjects of general interest. Nontechnical part will
cover book reviews. significant personal and technical accomplishments. current news and new products.

2.

Endorsement

Acoustic Emission Working Group (AEWG), European
Working Group on Acoustic Emission (EWGAE). Committee on
Acoustic Emission from Reinforced Composites (CARP), andAcoustic Emission Working Group of India have endorsed the
publication of Journal of Acoustic Emission.

3.

Governing Body

The Editor and Associate Editors will implement the editorial
policies described above. The Editorial Board will advise the editors on any major change. The Editor, Professor Kanji Ono. has
the general responsibility for all the matters. Associate Editors
assist Ihe review processes as lead reviewers. Mr. T.F. Drouillard
is responsible for the AE Literature section. The members of the
Editorial Board are selected for their knowledge and experience on
AE and will advise and assist the editors on the publiclition
policies and other aspects. The Board presently includes thefollowing members:

S.H. Carpenter
D.A. Dornfeld
P. Fleischmann
L. Golaski
M.A. Hamstad
H.R. Hardy. Jr.
R. Hill
I.V. Ivanov
P.Jax
T. Kishi
O.Y. Kwon
J.e. Lenain
S.L. McBride
W. Morgner
C.R.L. Murthy
H. Niitsuma
A.A. Pollock
T.M. Proctor. Jr.
I. RomanC. Scalae. ScrubyA. Vary
E. Waschkies
M. WeverslW. Whittaker
B.R.A. Wood

4.

(USA)
(USA)
(France)(Poland)
(USA)
(USA)
(UK)
(Russia)(Germany)(japan)(Korea)(France)(Canada)(Germany)(India)(japan)(USA)(USA)(Israel)(Australia)
(UK)
(USA)
(Germany)(Belgium)(USA)(Australia)

Publication

Journal of Acoustic Emission is published quarterly inMarch. June. September and December by Acoustic Emission
Group. 308 Westwood Blvd.- Box 364. Los Angeles. CA 900241647. It may also be reached at 5731 Boelter Hall. University ofCalifornia. Los Angeles. California 90095-1595 (USA). tel. 310825-5233. FAX 818-368-8309. e-mail: ono@seas.uc\a.edu

S.

Subscriplion

Subscription should be sent to Acoustic Emission Group.
Annual rate for 1995 or 1996 is US $96.00. For surface delivery.
add $8 in the U.S. and $11 for Canada and elsewhere. For air maildelivery to South America. add S18. Western Europe. add S25 andadd S30 elsewhere. Overseas orders must be paid in US currencies
wilh a check drown on a US bank. Inquire for individual (withinslitutional order) and bookseller discounts.

6.

Advertisement

No advertisement will be accepted. but announcements forbooks. training courses and future meetings on AE will be
included without charge.

ISSN 0730-0050 Copyright © 1995 Acoustic Emission Group

Coden: JACEDO

Printed in U.S.A.

Correlation of Acoustic Emission Felicity Ratios and Hold·
Based Rate Moments with Burst Strengths of Spherical
Graphite/Epoxy Pressure Vessels
Karyn S. Downs and Marvin A. Ramstad
Abstract

analyzed, and b) the AE generated during a secondary
loading or a hold at fixed load is believed to be predominated by local AE from higher stress regions rather than by
uniformly generated AE.

Thirty-two graphite/epoxy pressure vessels (260 mm
outside diameter) were evaluated using a sixteen channel
acoustic emission (AE) system. The vessels were proofpressurized to approximately 70% of the nominal vessel
burst strength. Later the vessels were pressurized to failure.
Acoustic emission data (85-325 kHz) were gathered during
the tests by non-resonant. small aperture sensors. The proof
pressure profiles were structured to allow calculation ofFelicity ratios (from subsequent pressure ramp cycles) andweighted event rate data (from holds at tixed pressure).
Correlations between these AE data parameters and vessel
failure pressures are presented for a subset of eleven vessels
which experienced consistent testing conditions. An area
location scheme based on hit arrival time analysis was used
to identify the tirst sensor hit for each event.

This paper reports on correlations between AE and theburst pressures of eleven filament wound graphite/epoxy
spherical pressure vessels. These eleven vessels were asubset of the 32 vessels constructed for a designed experiment to study the effects of variations in manufacturing
parameters on burst strength of composite pressure vessels.
The eleven vessels survived the proof pressure cycle (i.e.,
actual burst pressure> 70% of the nominal burst pressure)and experienced consistent testing conditions. Each vesselin the designed experiment had deliberate changes made inseveral of its processing variables, thus resulting in a considerable range of burst pressures (55% to 110% of nominal) compared to a vessel manufactured in the nominal
fashion. No intentional impact damage was incorporated
into any of the test vessels. The AE results reported here
are unique in the sense that sixteen independent AE channels were used resulting in a relatively high density of
sensors on the 260 mm outside diameter parts. This highsensor density provided local information on AE generation
throughout the vessel based on the arrival sequence of thehits from each individual AE event

I. Introduction
Application of acoustic emission (AE) technology forthe non-destructive evaluation (NOE) of fiber composite
vessels has gone on since the early I960s. Ramstad () 992)
summarizes some of these applications as well as other AE
applications for tiber/epoxy composites. Recent papers(Whittaker et aI.• 1989a; Whittaker et aI., 1989b; Ramstad,et a1.. 1992) have emphasized two particular aspects of a
proof test to focus upon the generation of the AE that ismost directly related to the eventual failure of the composite pressure vessel. The first type of test is the so-called
Felicity ratio test that was originally proposed by Fowler(1977). The second test is a hold test at constant pressure.
Because a great deal of AE is generated uniformly through()u\ a composite part when it is stressed for the tirst time,
both of these tests provide tWO benefits: a) the AE generated upon a subsequent loading or hold is significantly
smaller in quantity. and thus more readily measured and2. Experimental

2. J Test Vessel Construction
Aerospace-type graphite/epoxy pressure vessels wereconstructed on a liner/mandrel consisting of two 5083 aluminum alloy hemispheres 1.3 mm (0.050") thick whichwere gas tungsten arc welded at the equator. Each welded
liner was adhesively bonded to two aluminum alloy bosses.
A nominal 4.6 mm (0.180") thick composite wall was
filament wound with graphite fiber (Amoco T-40) preimpregnated with epoxy. One of the two bosses was monolithic, whereas the inlet boss had an internally threaded pon
opening. Figure ) shows a cross section of the test vessel.
Because the most typical failure scenario for a nominally
manufactured vessel is to rupture near either one of the twobosses. the entire AE test scheme concentrated on these twoareas for gathering and analyzing AE activity. The sixteen

Received 2 September 1995. K.S. Downs (Karyn.S.Downs@
den.mmc.com) is affiliated with Lockheed Martin. P.O. Box 179.
Denver, CO 80201 and M.A. Hamstad (mhamstad@du,edu) iswith Department of Engineering, University of Denver, Denver.
CO 80208 USA. This is based on a paper that was presented at
the Fifth International Symposium on Acoustic Emission from
Composites. AECM-5. Sundsvall. Sweden and was included in theproceedings volume published by The American Society for
Nondestructive Testing, Columbus. OH.
Journal of Acoustic Emission
Volume 13. Number 3/4

450730·005Ol9SI$S.00I1304S.()SS
Copyright@I99S Acoustic Emission Grouptest and yet ensure a repeatable acoustic contact, c) the
design allowed each sensor to be individually removed andre-installed without disturbing the others. and d) it incorporated a manually-operated, mechanical lead breaker for AE
checkout and vessel interrogation. A sensor alignment
guide I acoustic isolator (consisting of a hollow Tenon®
poly-tetra nuoroethylene [PTFE] cylinder) was screwed
into each tapped hole in the support rings. A spring [with aspring constant of 0.35 N/mm] was located between thesensor and sensor cap and provided the force [approximately 2.2 N] to keep the sensor in place. Apiezon M
grease provided acoustic coupling between the sensor andvessel. The lead breaker device held a standard mechanicalpencil (with 0.3 mm diameter 2H Pentel lead) so that it
pivoted in a horizontal plane about a vertical axis, thus
breaking the lead on the vessel surface. To minimize any
possible effects of fiber orientation on wave propagation,
each vessel was installed in the proof test fixture with an
external, fixed winding pattern feature in the samerotational location.

Boss with inlet port
AESensors

Fig. 1 Cross section of vessel and sensor location.

2.3 Test Equipment Description. Checkout. and Calibration
Table I lists the major test equipment used. The sensors were wideband, non-resonant sensors which have asmall aperture (6.4 mm dia.) and a displacement response
which is fairly nat with frequency so that the recorded
waveforms would not be distorted. Al1 proof tests wereconducted with a computer-controlled programmablepressurization system incorporating a servo valve with afeedback loop. All the equipment underwent a rigorouscheckout.. and in some cases re-calibration, prior to proof
testing as summarized in Table A in the Appendix. The
eight older channels performed in a manner dissimilar to
the eight newer channels in the AE measurement andrecording unit. Interestingly, the relationship between theolder and newer channel behavior was quite linear, and wasconsistent across the range of input signals. It wasarbitrarily assumed that the newer channels gave moreaccurate data, and during post-test data analysis all the raw
energy and duration data from the old channels werecorrected for their errors of approximately 44% and 8%,
respectively.

Fig. 2 Proof test fixture schematic.
AE sensors were arranged in two concentric rings
around each boss (four sensors in each ring).
2.2 Test Hardware
A special proof test fixture, shown in Fig. 2, wascreated to maximize AE test repeatability. Its four mostnoteworthy features were as follows: a) the only physicalcontacts with the test vessel were the inlet plumbing and thesensor faces, b) the sensors were spring-loaded against thevessel surface to allow vessel expansion during the proof

Table I Acoustic emission equipment used.

Item
AE Measurement andRecordin2 Unit
Preamplifiers with Bandpass
Filters
AE Simulator
Acoustic Emission Sensors
lWideband Non-resonant)
Software for subsequent AE
data analysis

Manufacturer
Physical Acoustics
Corooration
Physical Acoustics
Corporation
Acoustic Emission
Associates
Staveley Sensors, Inc.
Data Description, Inc.

ModellSpartan AT
1220A200B

Notes
16 independent channels; 85-325 kHz bandpass
filters; SA-DAO v. 3.62 software.
Filters have actual bandpass of 85-325 kHz vs.
vendor-supplied values of 100-300 kHz.

AES·II
CM0204PZI'
Data Desk
v.4.2
46

9.5 mm nominal outside diameter; 6.4 mm
aoerture; end mount microdot connection.
A commercial off-the-shelf statistical analysis
oacka2e for Macintosh computers.

--

6000

50
40

S
4000
~
&: 2000

20

.~

;f

Crosshatches Indicate Portions

6 of Profile (A) where AE was
30 S Monitored & Analyzed:
10o-+---,--~""-iIi;'-"'---.,r---~'" oo 15 30 45

e~

ll.

Ramp 0 to 48.3 MPa, andHold at 51.7 MPa 7-17 min.

Time (min)Fig. 3 Pressure profile (A) used in proof testing.

2.4 Use ofLead Breaks in Proof Testing
At least three lead breaks were performed on theequator of each vessel. pressurized to 0.69 MPa (100 psi).
immediately before the start of actual testing and after theconclusion of each test as a practical means of checking thesensor. couplant installation. and data acquisition unit
operation. The lead break values (for traditional AE
parameters such as peak amplitudes. hit duration. hit arrival
times. etc.) for each vessel were compared to previously
measured values to detennine if a problem existed. Also.
waveforms from two channels were recorded. reviewed.
and compared with a previously established database.
2.5 ProofTest Methodology
Each vessel had experienced no pressurization of any
kind prior to monitored proof testing. The typical proof
pressure and burst pressure for this vessel design manufactured in the nomina] fashion are 51.7 MPa and 76 MPa.
respectively. Figure 3 shows the Pressure Profile (A) used
for the eleven vessels. The ponions of the profile for which
AE was monitored and analyzed (for the purposes of thispaper) are indicated by the cross-hatched areas. Ramp rates
were 6.9 MPa/min (1000 psi/min) and 2.1 MPa/min.
Unload rates were 6.9 MPa/min or 20.7 MPa/min. [Note:
Figure 3 illustrates only the 6.9 MPa/min unload rate.]
Ho]d times were 17 minutes. Table 2 describes traditional
AE parameters measured and recorded.
Other data acquisition parameters for the AE measurement and recording unit were as follows; Preamplifier

Gain = 40 dB; System Gain = 26 or 36 dB (depending uponthreshold used); Hit Definition Time (HDT) 300 ~s; PeakDefinition Time (PDT) 150 ~s; Hit Lockout Time (HLT)=2000 ~.

==A discussion of the rationale for selecting a HLT of2000 ~s is appropriate. The equipment manufacturer
specifies that a HLT of 20 to 65.535 ~s is allowable by the
Spartan AT hardware. with a HLT of 100 to 300 J1s being
recommended for general purpose testing of composites
and non-metals (Physical Acoustics Corporation. 1992).
Thus, at first glance it may appear that the present HLT
selection of 2000 Ils is unusually long. However, this HLTvalue was chosen to minimize the chance that the lowamplitude (i.e., well below the set threshold) decaying tailend of one hit would be superimposed upon by another low
amplitude signal. thus resulting in a combined signal that
could cross the threshold and erroneously trigger a hit.
Post-test data analysis showed of the distribution of actual
arrival time differences between events showed that thisHLT choice was appropriate and was not problematic. For
the secondary ramps (up to the pressures at which Felicity
ratios were detennined), typically more than 98% of all
events occurred more than 3000 ~s apan (assuming a HLTof 200 Ils plus a typical hit duration of 1000 J1s). regardlessof the panicular channel hit. For the holds, at least 80%
and up to 98% of all events occurred more than 3000 ~s
apan. regardless of the channel hit. depending on the vessel
considered. Thus. the likelihood of multiple sequential
events actually hitting a single channel less than 3000 ~sapart during the tests described here was remote.

Table 2 Summary of AE data measured and recorded.
Portion of Profile (A)(Pressure Used)
Lead breaks
Initial Ramp (0 to 48.3 MPa)
Secondary Ramp (0 to 51.7 MPa)
Second Hold (51.7 MPa)

# Active 11u"eshold Notes: (40 dB gain at preamplifier for all tests)(dB)
Channels
16
36
Data not discussed in this oaoer.
2
60
Data not discussed in this paper. For correlations of
AE data with manufacturing parameters. see Downs
and Hamstad. 1995.
]6
48
Data collection was ceased at previous maximum
oressure (48.3 MPa) to orevent eauiDment saturation.
16
48
Data analyzed for 7-17 minutes of hold.

Additionally, it has been demonstrated that Spartan AT
units require a minimum of 445 J.ls after the completion of
the hit detection time (HOn before a unit is ready tocorrectly measure and record a subsequent hit (Hamstad
and Atkins, ]995). This minimum time for the Spartan AT
to be ready for a subsequent hit was experimentally determined with the unit operating in the "activity graph - highspeed" data acquisition mode. Thus, selecting any HLT ofless than 445 J.ls does not make sense, regardless of thematerial being tested.

subsequent loading divided by the previous maximum load
(ASTM EI067-89, 1989). The first step used to calculate
Felicity ratios for the test vessels was to establish six
primary definitions of "emission", or in other words, "AEactivity." Next, multiple quantitative definitions of "significant" were arbitrarily selected for each type of "AEactivity." The broad range of "significant" values chosen
was intended to span a substantial portion of the total
activity occurring during the secondary ramp. The "onsetof significant AE activity" was thus numerically defined as
the first instance at which the AE activity surpassed a"significant" value.

3. Results

3. J AE Dara for Second Ramp of Profile (A)A "most active channel" was determined for thesecondary ramp of each vessel, and was defined as the
single channel having the greatest sum of "firsr hits" at theapproximate pressures for which the FR was evaluated. In
other words, more AE source events originated within theregion of the sensor for the "most active channel" than
within the region of any other sensor. Finally, a Felicity
ratio was calculated for each vessel using each combinationof primary definitions, "significant" values. and "all channels" or "most active channe1." In all, ]49 Felicity ratio
values were calculated for each vessel.

The raw data were converted from the vendor software
used for AE data acquisition to ASCn (American Standard
Code for Information Interchange). The ASCII files were
imported into a commercial statistical analysis software
package, and analyzed using substantial quantities ofanalysis code custom written for this project within thiscommercial software. The hits from 16 independent channels were segregated into a sequence of individual eventsusing a scheme based upon their arrival times. First, thehits were sorted by arrival time. Then successive hits
greater than 80 J.lS apart and greater than 6 dB above thethreshold were assumed to belong to separate events; hits
greater than 150 1.1 s apart and less than 6 dB above thethreshold were also deemed to belong to separate events.
Otherwise, two successive hits were assumed to belong to
the same AE source event. The logic behind this two-tiered
scheme for grouping hits by source events was driven by
the assumption that hits having peak amplitudes substantially above the threshold likely triggered on the fastervelocity extensional mode of the wave; alternatively, hits
having peak amplitudes just slightly above the thresholdwere assumed to have triggered on the slower velocity
components of the flexural wave. This scheme was based
upon the examination of a few shorter data files by hand.

Attempts were made to correlate the values for eachdefinition of the Felicity ratio with the burst pressures forthe eleven vessels. Table 3 summarizes the FR definitionsand values used, and the quality of the predominantcorrelations of FR with burst pressure for each definition.
Nearly all of the FR definitions displayed a trend ofincreasing burst pressure with increasing FR. Additionally,in every case evaluated in which a trend was evident, thedata fell into two distinctly separate populations: seven"low burst" vessels (62-70 MPa burst), and four "highburst" vessels (74-8] MPa burst). Each population had alinear correlation of burst pressure to FR, although theslopes differed substantially for the two groups.
Figure 4 is a typical example (ranked "excellent") of
the linear correlations of FR with burst pressure for "lowburst" vessels and "high burst" vessels. The correlations
shown in Fig. 4 are all for the same FR definition (Le., the"onset of significant AE activity" occurred when the sum offirst hits from the "most active channel" surpassed 50 firsthits). The scale of Fig. 4a shows both correlations: Fig. 4bshows only the "low burst" data; Fig. 4c shows only the"high burst" data. Note that vessel "H" (a "low burst"
vessel) is always an outlying data point for every FR
definition where a trend or correlation was evident.

The logic of this overall scheme for grouping hits bysource events was successfully verified by computerchecking each data file to ensure that each event contained
no more than ]6 total hits, and that each channel was hit no
more than once within an event. It was noted that "firsthits" comprised 15-50% of all hits recorded. This is ofinterest because a substantial portion of the data analysis
that was performed focused on information only from "firsthits" (rather than from "all hits or total hits" which would
have included data from first hits and subsequent hits in an
event). Additionally, there was an average of 2.6 total hits
per event for "low burst" vessels (burst pressure of 62-70MPa), and an average of 4.5 total hits per event for "highburst" vessels (burst pressure of 74-81 MPa).

In most cases. the degree of correlation of the FR withthe burst pressure gradually changed as the "significant"value used in the primary FR definition was graduallychanged. Generally speaking for all FR definitions basedon sums or rates, the correlations were fair to good whenusing the "significant" values occurring at the lowest

The Felicity ratio (FR) has been defined as the load at
which the "onset of significant emission" occurs on a48

Table 3 felicity ratio definitions evaluated and summary of correlations with burst pressure.
Data from All
Channels"Si~nificant" Values:
Quantity
Range
of Valuesof Values
12
25 to
4000
15
10 to
1000
250
19

Felicity Ratio"AE Activity"
Definition

Cumulative Sum
of All Hits
Cumulative Sum
of "First Hits"
Cumulative Sum
of Energy Counts for
to"First Hits"
100.000
15
Average Energy
25 toCounts oer "First Hit"
500
9
50 to
Average Rate ofEnergy Counts per
500
Second for "First Hits"
0.5 to18
Avg. Rate of "First
Hits" per Second
12.5* P (poor) = No detectable trend
F (Fair) = Detectable trend; substantial scatter

4 (a)-;- 80 -

'I"

~ 7S·
~

<II

*

70 -

l 65 -

-=ri

60

0

00

ota
x

. .

• •
0.0 0.2 0.4 0.60.8 1.0
Felicity Ratio

70

Data from Single"Most Active Channel""Si~nificant" Values:
Range
Quantityof Valuesof Values
5 to 350
15

Burst
Pressure

Low

Hi2h
5t050

8

100

13

10

2900
25 to
1000
10 to
100

17
8

Low
Hieh
Low
High
Low
Hieh
Low

High

Quality of thePredominant Correlations*of Burst Pressure to FR:
All Channels"Most Act. Ch"E G F P E G f P
X X
- X X

- - - - X - X X X - X - - X X - - - - - X
X X X X X X X . X - - - - X X-

X- - - X - - - X X - - - X
X X - - X X X- - - X -

X
X

-

X

Low
X X X X
Notable toX
be evaluatedHieh
G (Good)= Dlstmct correlation; moderate scatter
E (Excellent) = Distinct correlation; minimal scatter
0

Cannotcalculate

-

- -

4 (b)
80

68

78

66
64
62
60

o "Low Burst" Vessels+ "High Burst" Vessels

76

x Vessel "H"74
72

0.2 0.4 0.6 0.8 1.0
felicity Ratio

0.95

0.97
0.99
Felicity Ratio

Fig. 4 Burst pressure vs. FR where "onset of significant AE activity" was defined as surpassing a sum of 50 "first hits" fromthe "most active channel": a) scale showing "low" and "high burst" vessels; b) only "low burst" vessels; c) only "high burst"
vessels.
pressures in the ramp (Le.• the smallest sums or the slowest
rates); the correlations quickly improved to be their best(either good andlor excellent) as the "significant" value was
gradually increased. In most cases. the correlations eventually degraded substantially when the "significant" values
were increased further still (to the highest sums and rates
examined). A typical example of this pattern. in which thequality of correlation graduaJJy changes with increasing"significant" values, is shown in Fig. 5. The fR vs. burst
pressure data shown in Fig. 5 is for "low burst" vessels
where the "onset of significant AE activity" was defined as
surpassing a particular sum of energy counts for first hits
from all channels. In Fig. Sa (where the "significant" value
equals 500 energy counts) an initial trend is evident; in Fig.
5b (2500 energy counts) the correlation is "good"; in Fig.
5c (7000 energy counts) it is "excellent"; in Fig. 5d (40,000
energy counts) the correlation has degraded to "poor".

As can be seen from Table 3, the quality of correlation
for some definitions of FR vs. burst pressure differed for"low" vs. "high burst" vessels. For example, there were notas many "excellent" rankings for "high burst" vessels. Also.
the correlations based on average-energy-counts-per-firsthit never improved past "poor" for the "low burst" vessels,
whereas the "high burst" vessels showed some "good" and"fair" results for this same fR definition. More notably,
results for "low burst" vessels using "most active channel"
data were consistently as good or better than results using"all channel" data; however, the opposite was true for "highburst" vessels. One imponant similarity was noted for"low" and "high burst" vessels; when examining results forcumulative sums of all hits and first hits, better correlationsof FR to burst pressure were obtained for "first hit" data vs.
"all hit" data.

49

_

5 (a)

70

70

5 (c)
5 (b)
70 _ - - - - - - - - - . .
........--;...;....-...,.

'-' 68
e 66

68

68

66

66

5 (d)
Fig. 5 All Views: 0
68 - 0 "Low Burst"
x Vessel "H" 0
66 ~~.;..;;;;;;~.=.:.--'

&:64

64

x

64

64-

62

r 2 :: 0.871

62

62-

~

~

... 62! 60

0r 2 ::: 0.643(excluding "H"

60 +-.--r-....(e..,.x..,cl...,udin,...·.,.;g.,."H.,."~

70

o

OX

o

....,..,• _ _r'
6O ......r-..-..,...r-..-..,.....r-"I"-t 60'-r't""'1........T"""I
0.0 0.2 0.4 0.6 0.8 1.0
0.0 0.2 0.4 0.6 0.8 LO
0.0 0.2 0.4 0.6 0.8 1.0
Felicity Ratio
Felicity Ratio
Felicity Ratio(2S00 Energy Counts)(7000 Energy Counts)(40.000 Energy Counts)

0.0 0.2 0.4 0.6 0.8 1.0
Felicity Ratio(500 Energy Counts)

Fig. 5 FR vs. burst pressure where "onset of significant AE activity" was defined as surpassing a particular sum of energy
counts for first hits from all channels: a) 500 energy counts; b) 2500 energy counts; c) 7000 energy counts; d) 40,000 energy
counts.

i 70

600

!68

66

64

64

r 2::: 0.782

6262

r 2 ::: 0.876{excluding "H"

60

60(excluding "H"

~66

£64
E 62
60

6~

0.0 0.2 0.4 0.6 0.8 1.0
Felicity Ratio(75 Hits; All Ch)

0.0 0.2 0.4 0.6 0.8 1.0
Felicity Ratio(50 Hits; "most active ch")6 (d)70 ..,.---------~ 70 -r---~~-_
68
68

68
66

en

~

70

66

64

62

r 2 ::: 0.998

60 ;-,,..,..-;(e~xr-c,..lu.,.di""lng::;.,,."H.,."~

0.0 0.2 0.4 0.6 0.8 1.0
0.0 0.2 0.4 0.6 0.8 1.0
Felicity Ratio
Felicity Ratio(20 1st Hits; "most active ch")(50 1st Hits; All Ch)

Fig. 6 Burst pressure vs. FR where "onset of significant AE activity" was defined by surpassing a particular sum of all hilS or"first hits": a) sum of 75 total hits from all channels; b) sum of SO total hits from the "most active channel"; c) sum of 50"first hits" from all channels; d) sum of20 "first hits" from the "most active channel."Figure 6 shows some of the patterns described above
for correlations of FR vs. burst pressure for "low burst"
vessels. For example, the "good" correlation in Fig. 6a(with the FR based on the sum of 75 total hits from allchannels) improves to "excellent" for Fig. 6b (sum of 50
total hits from the "most active channel"); similarly, the"good" correlation of Fig. 6c (with the FR based on the sumof 50 first hits from all channels) improves to "excellent"
for Fig. 6d (sum of 20 first hits from the "most active
channel"). thus showing the benefit of "most active
channel" data vs. "all channel" data. If a person were tocompare the "good" correlations of Fig. 6a and 6c (with 6chaving slightly less scatter than 6a), and the "excellent"correlations of Fig. 6b and 6d (with 6d having less scatterthan 6b), it is possible to detect some improvement incorrelation due to using "first hit" data vs. "all hit" data.
3.2 AE Data for Second Hold (at 5 J. 7 MPa) of Profile (A)All the data for the second hold were sorted into
separate events in the same manner used for the second
ramp data. First hits comprised 15-45% of all hits recorded. Additionally, there was an average of 3.4 lotal hits per

event for "low burst" vessels (burst pressure of 62-70 MPa),
and an average of 5.3 total hits per event for "high burst"
vessels (burst pressure of 74-81 MPa). Hamstad, Whittaker, and Brosey (1989b) first introduced the concept ofusing a time-weighted approach for examining the evolution of AE activity vs. time for its relationship to burst
strength. As was done by Hamstad, et al. (1989b), a rale
moment which was indicative of the rate and time at which
first hits occurred [i.e., the Event Rate Moment (EvtRM)]
was defined and evaluated. Additionally, a newly createdrate moment which was indicative of the rale and time atwhich energy counts for first hits occurred [i.e.• the Energy
Rate Moment (EngRM)] was defined and evaluated. Table
4 summarizes the definitions of these two Rate Moments.
Figures 7 and 8 show typical plots of the rate moments
vs. burst strength. More specifically, Figs. 7a and 8a show
rate moments calculated using first hit data from all channels; Figures 7b and 8b show rate moments calculated using
first hit data from the "most active channel" (i.e.• the channel with the greatest quantity of first hits); Figures 7c and8c show rate moments calculated using first hit data fromthe single channel having the greatest rate moment value.

Table 4 Definitions for time-weighted rate moments (holds at 51.7 MPa).
Numerical Dermition of Moment[1: First Hit Arrival times]+ [1: Quantity of First Hits];
where arrival time was 0-1 a min.
ll: (Arrival time)(energy counts)]+ ll: Quantity of First Hits];
where arrival time was 0-1 a min.

Moment Name
Event Rate Moment(EvtRM)

Energy Rate Moment(Ene:RM)
7 (a)-;80Q,j:E 7S - +-++~ 70 -~.. 6S -

0

= 60

•

~

+

70

•

60

•

+

+

......

65

\0

7 c

80

7S

0

0

7

80

T

Comments
Used first hit data only. Data was collected from 717 minutes of hold (thus labeled with arrival times ofa to 10 min.).
Used first hit data only. Data was collected from 717 minutes of hold (thus labeled with arrival times ofa to 10 min.).

+

75

+

70

0

0

~

65

~.o... Cl

220 240 260 280 300

EvtRM(all ch)

EvtRM(1 ch wi most 1st hits)

250

x' Vessel "H"

0

Xo

300

350

0

60

220 240 260 280 300

o "Low Burst" Vessels+ "High Burst" Vessels

400

EvlRM
(l ch wi greateslEvtRM)

Fig. 7 Burst strength vs. Event rate moment (EvtRM); EvtRM calculated using data from: a) all channels; b) the "most active channel", i.e., the single channel with greatest quantity of first hits; c) single channel with the greatest EvtRM value.

8 (a)~ 7S -

-

80-

+

~ 70-

,.
=

l.. 65 ~

0

0

60

0

20

+

+

0

+

7S 0

65

80

+

0

65 0

•

60

•

20

o0

0

+
0

0

40 60 80
EngRM
(1 ch wi most 1st hits)

0

+

70-

0

•

or

7S -

++

0

!o

60

•

80 -

T

70

40 60
EngRM
(all ch)

8 (c)

8 (b)

80

T

o "Low Burst" Vessels+ "High Burst" Vessels
x Vessel"Wx•

25 50 75 100 125 150
EngRM(1 ch wi greatest EngRM)

Fig. 8 Burst strength vs. Energy rate moment (EngRM); EngRM calculated using data from: a) all channels; b) the "mostactive channel". i.e.• the single channel with greatest sum of first hits; c) single channel with greatest EngRM value.
4.D~onofRendts

were imposed during the monitored portions of these test
periods. Additionally, this expectation was supponed by
the success of previous research on Kevlar®/epoxy vessels.
These previous efforts on Kevlar®/epoxy vessels usedsimilar test procedures and found a good correlation between burst strength and two types of AE activity, specifically the Felicity ratio (FR) and a time-weighted event rate
moment (Whittaker et aI.• 1989a; Hamstad et aI.• 1992).

The AE test procedures and data analysis were selectedbased upon the assumption that AE arising predominantly
from local flaws andlor higher stress regions will have abetter correlation with burst strength than uniformly generated AE. Since it is the combined influence of localized
flaws which ultimately controls a vessel's burst strength.
this appears to be a reasonable assumption. The test procedure was selected with the expectation that the AE generated and recorded during the secondary ramp and hold atpressure would consist substantially of AE arising fromlocalized damage being created andlor friction from damaged regions rather than uniformly generated AB. This
perspective is based on the fact that no new stress levels

There are many similarities and some important differences between the results presented here for graphite/epoxy
vessels vs. previous results for Kevlar®/epoxy vessels.
One similarity is that in both cases the FR was an indicatorof burst strength. The FR vs. burst correlations for graphite/epoxy, however, were substantially better than the51

Kevlar®/epoxy results. For graphite/epoxy vessels, thebest correlations were achieved for FR definitions calculated using "first hit" data from the "most active channel"
for vessels with burst pressures less than 70 MPa, i.e., "lowburst" vessels (e.g., Fig. 6d). Some observations regarding
the selective data analysis techniques used can explain this.
First, using "rlrSt hit" data as opposed to "all hit" data improved the correlations of FR to burst pressure for both"low" and "high burst" vessels, as can be seen by comparing Fig. 6c to 6a, and by comparing Fig. 6d to 6b. This
improvement is true for two reasons: a) the significance ofsums and/or rates of actual AE events (as they pertain tovessel integrity) is better represented by sums andlor ratesof "first hits" than by similar data for "all hits"; and, b) attenuation of the hit parameters for "first hits" presumably isless than the attenuation experienced by subsequent hits
within an event. If a FR definition is based upon hit parameters (such as energy counts), the resulting FR values
will be substantially affected by any attenuation. The attenuation in the composite vessels was substantial, as isevidenced by the low average number of sensors hit foreach event. Thus, this study selectively used only datafrom "first hits" when calculating FR values for those FR
definitions based upon energy counts.

ferent in character than the collective data from all thechannels.
Each of the three above observations demonstrates that
selectively focusing upon AE data arising from local flaws
can enhance the quality of the correlation for FR vs. burst
strength, especially for "low burst" vessels. This approachof selective data analysis (which focused on data from"first-hits" andlor from a "most active channel") was valid
only because of the high sensor density used. The quantityof sensors used effectively defines the quantity of distinct"vessel regions" for which one can separately analyze theresulting AE data. It is only when a meaningfully large
number of sensors is used that each resulting vessel regionis physically small enough to display distinctive and detectable differences in the character of the AE data recorded
from that localized region. Using fewer sensors (e.g., only
one or two as has often been done in the past on a test article of this size) would have substantially reduced the validity of using data from "first hits" andlor a "most active
channel". Also, multitudes of real, localized AE eventswould not have even been recorded because of the highsignal attenuation behavior of the co mposite.
Some scatter does exist even in the best correlations of

FR with burst pressure presented here. No specific reasons

Second, the "low burst" vessels were pressurized to agreater percentage of their failure strength during the initialramp (i.e., approximately 70% to 78% of burst), versus the"high burst" vessels (i.e., approximately 64% to 65% of
burst). This proportionally greater stress at the initial ramp
peak pressure likely caused greater stimulation of local
flaws in the "low burst" vessels than in the "high burst"
vessels. Therefore, the "low burst" vessels likely experienced a greater percentage of AE originating from thesepreviously stimulated flaws during the secondary ramp than
did the "high burst" vessels.

were detennined for the consistently outlying behavior ofvessel "H", a "low burst" vessel. However, the slight scatter in the remaining data points may be due to the fact thateach vessel experienced multiple and substantial changes in
its manufacturing parameters. Another reason may be that
the AE measurement and recording unit used has a threshold-based system for determining arrival times, and thistype of system does cause some errors in the recorded arrival times (Hamstad and Downs, 1995). How often theseerrors occur has not been established. However, the general
success of our FR correlations leads these authors to est imate that this equipment behavior resulted in errors in su bsequent determination of "first hits" less than 10% of thetime.

Third, using data from the "most active channel"(instead of the collective data from all channels) was ameans of selectively analyzing AE from the most active
region of the vessel. The use of 16 sensors (each individually connected to an independent data collection channel)
effectively created 16 separate regions of data for the vessel. Thus, the activity of each region could be examined
separately. Presumably the most active region had thegreatest stimulation of local flaws compared to other regions within each vessel. Interestingly, the "high burst"
vessels did not experience the same improvement in correlation by using data from the "most active channel." Oneexplanation for this may be that the proof pressures were
not proportionally high enough in the "high burst" vessels
to cause anyone particular region (not even the "most active" region) to have a notably larger proportion of AE dataarising from local flaws. Thus, the data from the "mostactive channel" of "high burst" vessels was possibly no di f-

Unlike the Felicity ratio correlations, the correlationsof rate moments to burst pressure were substantially different for graphite/epoxy vessels vs. Kevlar@/epoxy vessels.
Previous research on Kevlar®/epoxy vessels found a rather
linear correlation between event rate moment and burst
pressure, with burst pressure decreasing for an increasing
event rate moment (Hamstad, et aI., 1992). In other words,
having a larger proportion of events occurring later (rather
than earlier) in the hold was a sign of decreased strength. A
greater event rate moment value could be also be indicativeof a situation in which the rate of events gradually increased over time during the hold, as opposed to remaining
steady or decreasing. It makes intuitive sense that a more
quickly accelerating rate of AE activity occurring during ahold at pressure would be indicative of a weaker vessel.
52

Of the three Event Rate Moment (EvtRM) correlations
presented here for graphite/epoxy vessels, only the "lowburst" data points of Fig. 7b display a discernible trend(indicated by a dotted line in Fig. 7b) in the same fashion as
observed for Kevlar®/epoxy vessels. This general lack ofcorrelation for the graphite/epoxy vessels may. once again,
be attributable to the multiple changes in manufacturing
parameters in each vessel. A more likely explanation, however, is the difference in sensitivity to stress rupture for
Kevlar® vs. graphite fibers. Kevlar® fibers have beenfound to be more sensitive to static fatigue than graphite
fibers (Moore et aI., 1974). This implies that the
Kevlar®/epoxy vessels would be more prone to having localized flaws propagate earlier andlor more often in a given
hold at pressure as compared to graphite/epoxy vessels.
This potential for increased earlier AE activity arising fromlocal flaws in Kevlar®/epoxy vessels vs. graphite/epoxy
vessels may explain the better correlation of event rate
moment with burst pressure for Kevlar®/epoxy vessels vs.
graphite/epoxy vessels.
The Energy Rate Moment (EngRM) correlations
shown in Fig. 8 show a very slight trend of increasing burst
pressure with an increasing EngRM; Figure 8c displays aninteresting dual line structure for which no explanation has
yet been found. The general trend of increasing burst pressure with increasing EngRM is contrary to the trend observed for the EvtRM. Apparently, more energetic AE activity implies a stronger vessel. One possible explanation is
the smaller attenuation experienced by "high burst" vessels,
which thus could cause consistently greater mea-sured e nergy values for them. Although no significant correlation
trends were found in this study for hold-based AE rate moments and burst strength, successful quantitative correlations were obtained for other types of hold-based AE data
(e.g., quantities of long duration events and cumulative
sums of duration times) and burst strength. However. thesedata are not presented or discussed in this paper.
A few recommendations are appropriate when considering future AE monitoring of graphite/epoxy composites. First, it is important to establish an AE databaseunique to the component design and specific materials being tested. To be most effective, this database should include some test articles with low failure strengths, andshould preferably incorporate a broad range of failure
strengths. This is necessary to ensure that a sufficiently
broad range of data is available with which to establish ameaningful correlation of AE activity to burst strength.
Second, the rate moment approach appears to be much lesseffective for graphite/epoxy composites than for Kevlar®1
epoxy composites, and thus is not recommended. It is possible that increasing the length of the holds at pressure
might improve the correlations for graphite/epoxy, but thisalone may not be sufficient to counterbalance the relative
insensitivity of graphite/epoxy to static fatigue. Third, theFelicity ratio approach appears to be a superior method forcorrelating AE activity to failure strengths. Fourth, asshown by the results presented here. it is definitely beneficial to preferentially examine data solely from "first hits",
rather than the collective data from all hits. Some additional benefit may also be derived from further reducing thedata examined to that AE data occurring in the "most active" region of the test article. This implies the need for ahigh sensor density. Alternatively, equipment with an accurate source location capability could be used. but this is
not possible in the current threshold-based AE systems.
As for a FR definition recommendation, the best correlations in this study were obtained for rates of "first hits"
or energy counts from "first hits", and for cumulative sumsof hits (either all hits or "first hits") and energy counts from"first hits". Because the value of "average energy counts
per first hit" changed erratically during the ramp, the resulting FR values also changed erratically when the"significant" value was changed slightly, and thus did notconsistently give good results. FR definitions based onsums, however, were robust and showed a stable evolvement as the "significant" value was gradually changed.
which is not surprising given the fact that the inherent behavior of sums was less erratic. FR definitions based on
rates of AE activity were slightly more erratic that those
based on sums. The numerical data analysis required to
calculate rates of AE activity is, not surprisingly, more
complex than for cumulative sums. Therefore. theseauthors recommend that cumulative sums (of hits and/or
energy counts, and preferably using data solely from "firsthits") be examined initially.
Equally imponant in calculating a FR is selecting anappropriate numerical value for "significant" when determining the onset of "significant AE activity." This study
purposely examined an abundance of "significant" values inorder to detect resulting trends in the FR behavior andchanges in degree of correlation with burst pressure. One
reasonable methodology for future FR studies is as follows:a) First determine (for each test article) the total AE activity(i.e., cumulative sums of hits andlor energy counts, andpreferably using data solely from "first hits") occurring
during a secondary loading. starting from no load andceasing data collection upon reaching the previous maximum load. b) Determine the particular test article having
the least total AE activity (i.e., having the smallest sums).
[For reference, one should note that in this study the typicalsums for the least active vessels were an order of magnitude
smaller than the sums for the most active vessels.] c) Establish four to six "significant" values which span the rangeof the sums for the least active snicle. for example at 10%,
20%, 35%, 50%. 70% and 90% of the sums for the least
active test article. d) Use each of these "significant" values
to compute a Felicity ratio for each test snicle. e) Examine
the resulting correlation of FR vs. burst pressure for each ofthe "significant" values established. Potentially, they may
all give good correlations (as occurred in this study forsome FR definitions). More likely, however. is that thecorrelations resulting from one or two "significant" values
will stand out as being better than the rest. It may then be
appropriate to further examine a few more "significant"values that span the small range between (or that extend
slightly beyond) the two best "significant" values examinedpreviously.

"AE activity" when determining the FR value. Also,
the specific choice of a quantitative value for "significant" when determining "significant AE activity" in defining the FR greatly affected the resulting degree ofcorrelation of burst pressure with FR.

6.

Lastly. it is the recommendation of these authors that ahigh sensor density be used. If typical failure modes are
known prior to testing. then the sensors can be selectively
placed near the anticipated areas of failure, as was done inthis study, to minimize the total number of sensors required.
Having a larger number of sensors increases the resulting
precision of the data analysis. This improved precision ispossible because the data from each of many smaller.
physical regions of the test article can be separately analyzed. Thus, it makes the selective examination of datafrom "first hits" and a "most active" region more meaningful. This is important since use of such data appears to givethe best correlations by substantially reducing data scatter.
Additionally. a high sensor density helps to counteract thehigh degree of AE signal attenuation typical in graphite/epoxy composites.

relations which were also good. but which wereslightly less stable than correlations from FR definitions based on sums of AE activity. FR definitions
based on AE-activity-per-hit produced correlations
with an erratic degree of fit.
7.

The correlations of burst pressure to two rate moments(specifically the Event Rate Moment and Energy Ratemoment) calculated from AE data gathered duringholds at fixed pressure were generally poor for thegraphite/epoxy vessels studied here. This is in contrast
with previous work using an event rate moment for
Kevlar®/epoxy vessels.

Acknowledgments

The authors thank Jamisen Jensen and Robert Laueroth(Brunswick Composites) for their proof pressure tests;

S. Conclusionsl.

FR definitions based on sums of AE activity gave lhemost "robust" correlations of burst pressure to FR. FR
definitions based on rates of AE activity produced cor-

The correlations of burst pressure to Felicity Ratio

Dave Sheahan (Lockheed Martin) for test fixture design,(FR) were frequently excellent for the graphite/epoxy
vessels studied here. This is similar to previous workon Kevlar®/epoxy vessels.

Mack Roberts (Lockheed Martin) for the design-of-experiment results, and Lawrence Loechel (Lockheed Martin) and
Vincent Johnson (WPAFB) for their support of the COPV
Task 6 program. The effort described herein was sponsoredby the following agency: Manufacturing Technology Directorate, Wright Laboratory, Air Force Materiel Command (ASC), United States Air Force, Wright-Patterson
AFB, Ohio 45433-6533.

2

The best correlations of burst pressure to FR were Ii near for both "low burst" vessels (62-70 MPa burst) and"high burst" vessels (74-81 MPa burst), although thecorrelation slopes differed substantially for the two
populations of vessels.

3.

Using a high sensor density allowed meaningful anal ysis schemes which selectively examined data from"first hits" and a "most active channel." Since attenuation of AE signals within the graphite/epoxy composite
was substantial (with typically only 2.6 to 5.3 of the 16
AE sensors being hit by significant amplitude events),
the high sensor density also maximized the opportunity
to record information from a greater quantity of events.

References

4.

5.

American Society for Testing and Materials (ASTM)
E1067-89 (1989). "Standard Practice for Acoustic Emission
Examination of Fiberglass Reinforced Plastic Resin (FRP)
Tanks and Vessels," ASTM, Philadelphia
K.S. Downs and M.A. Hamstad (1995), "Relationships ofComposite Manufacturing Parameters of Filament Wound
GraphitelEpoxy Vessels to their Acoustic Emission Characteristics." Closed Session Proc. of SAMPE 40th International Symp., Anaheim. CA, The Society for The Advancement of Material and Process Engineering. Covina,
CA. pp. 1-15.

Substantial reductio ns in data scatter were achieved forcorrelations of burst pressure to FR when selectively
analyzing data solely from "first hits". Additional improvements in the correlation of burst pressure to FR
were achieved for "low burst" vessels when further reducing the data analyzed to that from a "most active
channel"TJ. Fowler (1977), "Acoustic Emission Testing of Fiber
Reinforced Plastics," Preprint 3092. American Society of
Civil Engineers. New York.

The specific degree of correlation of burst pressure to
FR was highly dependent upon the definition used for54

Physical Acoustics Corporation (1992), "Spartan AT User's
Manual," Rev. 1.1. June 1992. p. 6.

M.A. Hamstad (1992). "An Examination of Acoustic
Emission Evaluation Criteria for Aerospace TypeFiberlPolymer Composites," Proc. AECM-4, The American
Society for Nondestructive Testing, Columbus, OH, pp.
436-449.

l.W. Whittaker, W.O. Brosey, and M.A. Hamstad (1989a),"Correlation of Felicity Ratio and Strength Behavior of
Impact-Damaged Spherical Composite Test Specimens,"

Proc. Third International Symposium on Acoustic Emission
from Reinforced Composites, Paris. France. The American

M.A. Hamstad, l.W. Whittaker. and W.O. Brosey (1992),"Correlation of Residual Strength with Acoustic Emission
from Impact-Damaged Composite Structures underConstant Biaxial Load," J. Composite Materials, 26(15).
2307-2328.

Society for Nondestructive Testing, Columbus, OH, pp.
160-167.
l.W. Whittaker, W.O. Brosey, and M.A. Hamstad (1989b),"Correlation of Felicity Ratio and Strength Behavior of
Pneumatically and Hydraulically Loaded Spherical
Composite Test Specimens," Proc. Third International

M.A. Hamstad and K. Atkins (1995), Unpublishedresearch, National Institute of Standards and Technology,
Boulder. Colorado, March.

Symposium on Acoustic Emission from Reinforced
Composites, Paris, France, The American Society for

M.A. Ramstad and K.S. Downs (1995), "On Characterization and Location of Acoustic Emission Sources in RealSize Composite Structures - A Waveform Study," J.
Acoustic Emission, 13(112),31-41.

Nondestructive Testing, Columbus. OH, pp. 168-179.
Note: Reference to a company or product name herein
does not imply approval or recommendation by Lockheed
Martin or the United States Air Force to the exclusion ofother products that may be suitable.

R.L. Moore. M.A. Hamstad. and T.T. Chiao (1974),"Stress-Rupture Behavior of Graphite FiberlEpoxy Strands,
Composite Materials and Structures. 3(1), 19-23.

Appendix
Table A Summary of equipment checkout and findings.
Feature Checked orRe-calibrated
Uniformity of signal response
Sensors(peak amplitude and wave
shaDe)
Preamplifiers 3 dB highpass and lowpass
down points with 40 dB gainon the preamplifier
Preamplifiers 40 dB and 60 dB gain settings
Item

Checkout Method Used andlor Notable Findings
Performed lead breaks 152 mm (6 in.) away from sensors on graphite epoxy
plate (5mm x 0.45m x 0.45m). All sensors had similar wave shape and peak
amDlitudes ± 10%.
Determined actually to be 85 kHz (highpass) and 325 kHz (lowpass) Ys.
vendor-supplied values of 100kHz and 300 kHz.

Re-calibrated settings using RMS meter and oscillator with attenuation
features.
Saturation point (i.e., incoming Input signals at increasing rates from AE Simulator into AE measurementAE
unit. Saturation point 300 hitsls for single channel. 500 hitsls for all
Measurement data rate at which unit is no& Recording longer able to record all of the channels together. After saturation point, data collection substantially
incoming data); Manner incontinues on odd numbered channels (i.e., Ist channel of 2 on each
Unitwhich data beyond saturation Independent Channel Controller [ICC] board); but slows dramatically or
point is omitted from recorded ceases on even numbered channels (Le., 2nd channel of 2 on each ICC
board).
files
Set sensor on foam (with sensor acoustically coupled only to ambient air).
Background noise thresholdAE
Measured each channel separately. Noise threshold 22-26 dB for each
Measurement with 40 dB gain at thechannel (on average). (i.e., highest threshold at which unit begins recording& Recording preamplifier
data from backlrround noise)
Unit
Performance of all 16 channels Input shaped, simulated AE bursts. Each burst had a fixed frequency and theAEamplitude was varied. Input bursts from AE Simulator into 4 channels at a
Measurement (Le., does each channel
time of AE measurement unit. Older channels (digital v. 5C. analog v. 6C)& Recording measure and record data in aUnitsimilar. uniform manner given were all similar to each other. Newer channels (digital version 50, analog v.
70) were all similar to each other. Energy counts were dramaticallythe same input signals?)different (44%) for older channels ys. newer channels. Hit durations varied
sli2htlv (8%).

=

=

!is

Correlation of Regions of Acoustic Emission Activity with
Burst Locations for Spherical Graphite/Epoxy Pressure
Vessels
Karyn S. Downs and Marvin A. Hamstad
Abstract

resultant failure pressure of several graphite/epoxy filament
wound pressure vessels. Also, a lack of correlation wasshown between hold-based AE during the same proof test
and the failure pressure. Since a rather large number of
sensors was used in an independent mode during these AE
monitored proof tests. the data gathered provide an opportunity for a closer look at local variations in the AE generated during these tests. In particular, several questions may
be studied. First, do the most active local regions of generation of AE correspond to the eventual failure location?
Second. are the most active local regions the same for the
Felicity ratio data as for the hold AE data? Third, howdistinctly different are the local AE generation rates (forseparate channels within anyone vessel), and how extensiveis the propagation of this local AE? If fewer AE sensors
had been used. would the same overall conclusions arxI
correlations with burst pressure be obtained? The purposeof this paper is to present relevant AE data to attempt toanswer these questions and to come to conclusions relevantto the development of more efficient techniques of using
proof-test-generated AE to predict eventual failure pressuresor operational lifetimes of fiber/epoxy composite pressure
vessels or structures.

A sixteen channel acoustic emission (AE) system wasused to evaluate thirty-two graphite/epoxy pressure vessels(260 mm outside diameter) during a proof-pressure test to
approximately 70% of the nominal vessel burst strength.
Later the vessels were pressurized to failure. AE data (85325 kHz) were gathered during the tests by non-resonant,small apenure sensors. AE data were examined (for a subset
of eleven vessels which experienced consistent testing conditions) in terms of the cumulative AE activity occurring oneach individual channel during a secondary pressure ramp
and a second hold at fixed pressure. For each vessel. theprobable vessel failure location was compared to the ge0graphic region of the "most active" sensor for three points
of interest in the proof test: early in the second ramp (i.e.,near pressures at which Felicity ratios were determined).
near the end of the second ramp (i.e., at the previous
maximum pressure), and for the second hold at pressure.
Results showed that for lower strength vessels there was
generally a good match between probable failure locationand the specific geographic sensor regions which had thegreatest cumulative "first hit" AE activity at Felicity-ratiotype pressures. No similar match was found for higher
strength vessels. No consistent correlation was foundbetween the probable burst location and most active regionsof AE activity occurring at higher pressures in the second
ramp or during the second hold. regardless of burst strength.
It was also discovered that efforts to assess the significanceof the AE data are substantially influenced by the effects ofgeometric attenuation.

2. Experimental

2./ Test Vessel Construction
Filament-wound, aerospace-type graphite/epoxy pressure vessels were constructed as described by Downs andHamstad (1995). Figure 1 shows a cross section of the test
vessel. Because the most typical failure scenario for anominally manufactured vessel is to rupture near either oneof the two bosses, the entire AE test scheme concentrated
on these two areas for gathering and analyzing AE activity.
The sixteen AE sensors were arranged in two concentricrings around each boss (four sensors in each ring).

1. Introduction
In a companion paper (Downs and Hamstad, 1995),
correlations were presented between the acoustic emission(AE) based Felicity ratio (FR) from a proof test and theReceived 2 September 1995. K.S. Downs (Karyn.S.Downs@
den.mmc.com) is affiliated with Lockheed Martin, P.O. Box
179. Denver. CO 80201 and M.A. Hamstad (mhamstad@du.edu)
is with Department of Engineering, University of Denver.
Denver. CO 80208 USA. This is based on a paper that waspresented at the Fifth International Symposium on Acoustic
Emission from Composites. AECM-5, Sundsvall, Sweden andwas included in the proceedings volume published by The
American Society for Nondestructive Testing, Columbus, OH.
Journal of Acoustic Emission
Volume 13. Number 3/4

2.2 Test Hardware
A special proof test fixture, shown in Fig. 2, wascreated to maximize AE test repeatability. Further details
on the uniqueness of this fixture are described elsewhere(Downs and Hamstad, 1995). To minimize any possible
effects of fiber orientation on wave propagation. each vessel
was installed in the proof test fixture with an external. fixed
winding pattern feature in the same rotational location (at (J'5&073().()()50195ISS.00I13056-066

Copyright\!)1995 Acoustic Emission GroupTable I Summary of location and labels used for the 16 sensors.
North Equator
South Equator
Sensor Region &North Pole
South Pole
(49.7° North(49.7 ° South)(60.8° North(60.8° South
Latitude (eauator =0°)12
I I 2 I 3
4
Sensor/Channel #9 I 10 I II
16
5 I 6 I 7 I 8
13 I 14 I IS
DCj1;recs Lonl!itude*
15 I 105 I 195 285 60 I ISO I 240 330 60 I 150 I 240 I 330 15 I 105 I 195 285• LongItude Angles: Degrees clockWIse from filament Winding feature when Viewed from the North Pole.

North Pole Boss with inlet port
AE Sensors (4)(North Pole)
North Equator~
AE Sensors (4)JSouth Equator
AE Sensors (4)South PoleAE Sensors (4)Monolithic Boss
(South Pole)Fig. I Cross section of vessel and sensor location.

1500
Vl

Fig. 2 Proof test fixture with vessel partially installed.

3 (a)

1500

3 (b)

0
:l

.-::: -a

:I: > 1000... .c

1000

~~

500

o u

0_

500

=
50
60
70
80
90
100
Raw Peak Amplitude Distribution (dB)

50
60
70
80
90
100
Smoothed Peak Amplitude Distribution (dB)

Fig. 3 Typical peak amplitude distributions for all tests: a) before smoothing; b) after mathematical smoothing.
Longitude). Table I summarizes the location and identification labels used for the 16 sensors.

alternating higMow quantities for adjacent even/odd amplitude values. During post-test analysis. peak amplitude distributions were mathematically smoothed (and the individual
hit data were corrected). which reduced the amplitude resolution to 2 dB. Figure 3 shows typical raw and smoothed
distributions.

2.3 Test Equipment Description, Checkout. and Calibration

The major test equipment used is de5Cribcd elsewhere(Downs and Hamstad. 1995). The sensors were wideband.
non-resonant sensors which have a small aperture (6.4 mmdia.) and a displacement response which is fairly Oat withfrequency. All the equipment underwent a rigorous checkout. and in some cases re-calibration. prior to proof testing(Downs and Hamstad. 1995). One of the anomalies discovered in the performance of the AE measurement system
is relevant to the discussion presented here: for all tests for
all channels. the peak amplitude distributions had the same

2.4 Use of Lead Breaks in Proof Testing

At least three lead hreaks were performed on the equatorof each vessel. pressurized to 0.69 MPa (100 psi). immediately before the start of actual testing and after the conclusion of each test as a practical means of checking the sensor. couplant installation. and data acquisition unit operation. The lead break values (for traditional AE parameters
51

.-.
.;;)
Q.
'-'

.-.

50 CIS
~
40

6000

6
30 e

e 4000

::l

en
en

eu

It

20

2000

10
30
45
Time (min)

60

75

::l

en

£

Crosshatches Indicate Portions ofProfile (A) where AE was Monitored &Analyzed: the 0-t0-48.3 MPa portion ofSecond Ramp; and the 7-to-17 minuteportion of Second Hold (51.7 MPa).

0

Fig. 4 Pressure Profile (A) used in proof testing.
Table 2 Summary of AE data monitored and analyzed.
Segment of Profile (A)(Pressure)
Second (i.e., FR) Ramp
CO to 51.7 MPa)
Second Hold for 17 min.
(51.7 MPa)

# Active
Channels
16

Threshold

16

48

(dB)

48

such as peak amplitudes, hit duration, arrival times, etc.)
were compared to previously measured values to determine
if a problem existed.

2.5 Proo/Test Methodology
Each vessel had experienced no pressurization of any
kind prior to monitored proof testing. The typical proof
pressures and burst pressures for this vessel design manufactured in the nominal fashion are 51.7 MPa and 76 MPa,
respectively. Figure 4 shows the pressure profile (A) used
for the eleven vessels. The portions of the profile for which
AE was monitored and analyzed (for the purposes of thispaper) are indicated by the cross-hatched areas. Table 2 describes the the AE data which were monitored and analyzed
for the second ramp and hold.

3. Results
3./ AE Data/or Second Ramp of Profile (A)The raw data were converted from the vendor software
used for AE data acquisition to ASCII (American Standard
Code for Infonnation Interchange). The ASCIt files were
imported into a commercial statistical analysis software
package, and were analyzed using substantial quantities ofanalysis code custom written for this project within thiscommercial software. The hits from 16 independent channels were segregated into a sequence of individual eventsusing a scheme based upon their arrival times. First, thehits were sorted by arrival time. Then successive hits
greater than 80 I!s apart and greater than 6 dB above thethreshold were assumed to belong to separate events; hits
greater than 150 I!s apart and less than 6 dB above thethreshold were also deemed to belong to separate events.
Otherwise, two successive hits were assumed to belong toPortion of Segment of Profile (A)For Which AE Was Monitored & Analvzed
Data collection was ceased at previous maximum
Dressure (48.3 MPa) to Drevcnt equipment saturation.
Data analyzed for the last 10 minutes of the second holdCLe. the 7-to-17 minute portion of second hold).
the same AE source event. This scheme was based upon
the examination of a few shorter data files by hand. The
logic of this scheme was successfully verified by computerchecking each data file to ensure that each event contained
no more than 16 total hits, and that each channel was hit no
more than once within an event. It was noted that "firsthits" comprised 15-50% of all hits recorded. Additionally.
the average number of hits per event for the second ramp
(i.e., what we call the Felicity ratio ramp) ranged from 2.1(vessel I) to 6.1 (vessel 2-11) for the eleven vessels, thus
indicating substantial AE signal attenuation within thecomposite vessel. If attenuation had been much lesssubstantial, one would have expected most events to hit all
16 sensors.
For each vessel, a plot of AE activity vs. pressure wasprepared for the second ramp (0 to 51.7 MPa). Specifically,
the AE activity was separated into the cumulative sum of"first hits" received on each of the 16 channels and thenploned vs. pressure (up to 48.3 MPa, since data collection
was ceased at that point in the second ramp). By plotting
the AE activity for each channel individually, one could
separately consider the pressure-related trends of the AE
activity occurring within each of the 16 geographic regionsof the test vessel as defined by the sensor placement.
Figure 5 shows these "first hit" geographic regions existingaround each sensor; the inherent assumption in Fig. 5 isthat AE waveform velocities are nearly unifonn in all
directions on the vessel, as was demonstrated by lead breaktests. Any AE source event occurring within a given region
shown in Figure 5 should first hit the sensor shown withinthat region. Each polar region was 6150 mm 2 in area,
whereas each equator region was 20.730 mm 2 in area.
Thus, when comparing data from individual sensors, it ismore appropriate to compare only polar sensors to polar
sensors. and equator sensors to equator sensors. This is5 (c)

5 (b)

5 (a)

t

120mm

1

J

138mm

J

<

>-

205mm

Fig. 5 Schematic showing "first hit" geographic regions around each sensor: a) whole spherical view with some specificsensors shown; b) 2-dimensional projection of polar sensor region; c) 2-dimensional projection of equator sensor region.

6 (a)500-r---------""T""-,
North Pole Channels......
",Ci
South Pole Channels::: c: 400
:I: =
CI:I

.... ..!!!
o 0>.Cl.o.::: ..c

=

-

U

'" =
c 400

6~

North Equator Channels- - South Equator Channels:I:].!:: ....

300

u.,9
'- as

I

300

I
I

o =

>.cr
_U,l

200

.::: .c

= as

C,)

as
~U,l

CI:I

0=0

O~

I
I

200

/
/,,~

C,)

=U,l

100
..... :;;JI

...."

7 (a)

......

.-="'Uc
:I: =
CI:I

~.c

•!:: Uu., ..

.... ..!!!
o 0

.=
=

>.Cl.o

.c

C,)
as
~U,l

......

50

U#15, 10, 11 I
I
North
Pole
Channels40
I '- - South Pole Channels
I.,30
Sensor numbers arelisted from greatest
20
to least activity.

.= =
c
:I:]
-u
.~ ...
u.,9

10

CI:I

CI)

'- as

o =
~~

-== ..c
c:s
=U,l
0=0

-

0=0

...."

---

0

40

42

44
46
Pressure (MPa)

48

,

#8

~u

~.c

.!:: U
U. ..

6 (b)

...... 500

~~~
.,--

7 (b)
50

#1,5,7,6
North
Equator
Channels40- - South Equator Channels
30
Sensor numbers arelisted from greatest
20
to least activity.

C,)

10

.......

0-- --40

42

46
44
Pressure (MPa)48

Fig. 7 Plot of cumulative sums of "first hits" vs. pressure during FR ramp for Vessel 2-11: a) polar channels only; b)equator channels only.
particularly true because more of the "first hit" signals
which reach an eq~tor sensor may have traveled a greater
distance in the composite, and thus it may be more greatly
attenuated than a "first hit" signal received by a polar
sensor.
Figure 6 shows a plot of individual channel data of
cumulative sums of "first hits" vs. pressure (for vessel C2)
for the secondary ramp of Profile (A). Figure 7 shows

similar data for vessel 2-11. These two vessels were chosen
since they represent a lower burst strength (C2) and amoderate-te-higher burst strength (2-11). A "most active"
channel was defined as the single channel having thegreatest cumulative sum of first hilS at the pressure (or time
during a hold) of interest. One should note in Figs. 6 and 7
how the channel number of the "most active" channel
happens to change during the ramp.

:r: :;=
tI:lC)

-

8 (a)

150

North Pole Channels- - South Pole Channels

125

."=

... ..c
.~ U

100

.~

7S

....

«l

75

50

": ..c
e u

50

-

25

-

»c..

..: : .c-e «lu§t.t:I
C/e
0-

North Equator Channels- - South Equator Channels ,..#8 ...

C).-=tI:l ec

125....~o 0~

8 (b)

150

::c~

... u 100
...

~.9

o ='
~tif

§~
<:::Ie

25

0

0

",.

..4#6 "/,," .... -#5,," _ .... ~,,~-417-/;'"" ",,-r,,~~-;~-;~/.. ~~... t ....

00

100 200 300 400 500 600
Time (seconds)0"..".-r'"

100 200 300 400 500 600
Time (seconds)

Fig. 8 Plot of cumulative sums of "first hits" vs. time during the monitored portion of the second hold for Vessel C2: a)polar channels only; b) equator channels only.

:r: :;=
tI:lC)

.~

600
500

9 (a)
North Pole Channels;- - South Pole Channels ,.. ~/- ..c.~U 400- 300/

t.I.. ~....o 0»Cl..

.::: .c:

~

=

- ell
u 200
§t.t:IC/e 100

- o

"
/.. "

#15
.

""

#10

C)

tI:l

e

.-=:: c

::c~

U;U

~!:

11

-

9 (b)

200
150

&-t

~.9

....

CIS
o ::l 100~tif"=e .cu«ll:l:I::It.t:l50<:::Ie0.......

0o0~"'I""""'...-.r--r"""''''''''''''''''''''''''''''I''''""'-r--~

100 200 300 400 500 600
Time (seconds)

0

100 200 300 400 500 600
Time (seconds)

Fig. 9 Plot of cumulative sums of "first hits" vs. time during the monitored portion of the second hold for Vessel 2-11: a)polar channels only; b) equator channels only.

3.2 AE Data for Second Hold (at 51.7 MPa) ofProfile (A)All the data for the last 10 minutes of the second hold(i.e., the 7-to-17 min. portion) were sorted into separate
events in the same manner used for the second ramp data.
First hits comprised 15-45% of all hits recorded. Additionally, the average number of hits per event for the monitored portion of the second hold ranged from 2.2 (vessel I)
to 6.4 (vessel 2-11) for the eleven vessels. Figure 8 (vessel
C2) and Fig. 9 (vessel 2-11) show plots of cumulative
sums for individual channels of "first hits" vs. time for thesecond hold; these are the same two vessels analyzed for the
FR ramp (shown in Figs. 6 and 7).

4. Discussion of Results
Excellent correlations were obtained between burst
pressures and Felicity ratios detennined from the second
ramp (Downs and Hamstad, 1995). However, no significant
correlations were obtained for burst pressures and AE datafrom the second hold (Le., time or energy weighted rate
moments). Because substantial improvements were obtained

for the correlations of the Felicity ratio with burst pressure
when selectively using "frrst hit" data from the single "mostactive" channel for the lower burst strength vessels, one
might suspect there may exist a correlation between theprobable actual burst location and the "most active" regionof the vessel.
The relationship between the most active local regionsof the composite and the eventual failure location was
examined. First, the polar and equator sensors nearest to themost probable failure location were detennined for each of
the two example data sets used in this paper (i.e., vessels
C2 and 2-11). (11te probable burst locations were determined by visual examination of the burst vessels. lbe
accurate assessment of the failure origin locations was mademore difficult by the thinness of the metal liner. fraying of
the composite material near the area of failure, and thefrequent separation of the liner from the composite upon
failure.) Next, a "most active" channel was defined as the
single channel having the greatest cumulative sum of "firsthits" at a particular point of interest. Then, the four "mostactive" polar and equator sensors were detennined for both(corresponding to eventual failure locations) generated
during the initial ramp of the proof test. Hence, when
considering case (a) defined above and shown in Table 3(i.e., during the lower pressures of the FR ramp) for lower
burst vessels, the AE generated from these localized, moredistinctly-damaged zones has a more dominant influence on
the total "first hit" AE than the uniformly-generated AE
occurring within the same geographic sensor region. For
case (b) defined above and shown in Table 3 (i.e., at higher
pressure levels in the FR ramp), the generation of AE
begins to increase rapidly within all the geographic sensor
regions as the pressure increases. This rapid AE generationis composed primarily of uniformly-generated AE rather
than localized, damage-based AE. Thus, at higher pressuresthe localized damage-based AE is insufficient in quantity(compared to the uniformly-generated AE) to make thegeographic sensor region which contains the localized
distinctly-damaged zone distinguishable from othergeographic regions. Hence for case (b) (i.e., at higher
pressures in the FR ramp), the "most active" geographic
sensor regions are simply those that are generating thegreatest quantity of uniformly-generated AE, as opposed tosignificant quantities of localized damage-based AB.

vessels for three different cases: (a) during the FR ramp
(Figs. 6 and 7) at the pressure for which the FR was
detennined; (b) during the FR ramp (Figs. 6 and 7) at theprevious maximum pressure (48.3 MPa); and, (c) at theconclusion of the monitored portion of the second hold(Figs. 8 and 9). Several interesting results were observed.
First, for vessel C2 the sensors nearest the most probable failure location (i.e., polar sensor #13 and equatorsensor #5) matched directly with the "most active" sensors
detennined for case (a) described above (i.e., during the FR
ramp at the pressure for which the FR was determined).
Second, in contrast to this result, there was no such matchfor vessel 2-11, i.e., the most active sensor regions at the
FR pressure (#13 and #7) did not correspond to the sensors
nearest the probable failure location (sensors #12, #9, #4).
Third, for both vessels C2 and 2-11, the sensor regions
having the greatest cumulative "first hit" AE activity forcase (b) (i.e., during the FR ramp at the previous maximum
pressure) did not correlate with the probable burst location.
Fourth, for both vessels C2 and 2-11. the "most active"
geographic sensor regions for case (c) (i.e., at the end of thesecond hold) did correspond for the most part with the "mostactive" regions for case (b) (i.e., during the FR ramp at theprevious maximum pressure). To test if these conclusions
were valid over the larger data set, Table 3 was constructed
for all eleven vessels under consideration. Examination of
Table 3 indicates that with some exceptions the results
described are generally true. That is, lower burst vessels(e.g., Q, C2, H) generally follow the behavior described for
C2, whereas moderate or higher burst vessels (e.g., I and 2II) generally follow the behavior of 2-11. The two partial
exceptions (higher burst vessels 2-03 and 2-05) are notunexpected when the rest of the discussion presented here isconsidered. With these results in mind, it is not surprisingthat the best correlations of FR and burst pressure wereobtained for lower burst vessels when the "first hit" datafrom the single "most active" channel were used. Conversely, the "first hit" data from all sensors (not the single"most active" sensor) gave better correlations for higher
burst vessels than the data from the single "most active"
sensor (Downs and Hamstad, 1995).

For higher strength vessels, on the other hand, the initial ramp is less likely to sufficiently stimulate the generation oflocalized damage. Hence, the "most active" geographic sensor regions of higher burst vessels even during theearly part of the FR ramp [i.e., case (a)] do not correlatewith the eventual probable failure location. In essence, thisfact implies that the correlations of FR with failure pressure
for the high burst vessels were successful, as described in
Downs and Hamstad (1995), based upon data from uniformly-generated AE rather than from localized damage-based
AE. Thus we conclude in this case that the uniformlygenerated AE was indicative of the general overall quality of
the composite material.
Interestingly, the "most active" geographic sensor regions are the same for both lower and higher burst vessels
for case (b) and case (c) defined above and shown in Table 3,thus indicating that the "most active" regions of uniform
AE generation typically remain the same for the later portion of the FR ramp and for the second hold. We conclude
that this result is true for both lower and higher burst vessels because of the fact that graphite/epoxy composite is
known to have small sensitivity to stress rupture (Moore. etaI., 1974). If graphite/epoxy had greater stress rupture sensitivity, it might be expected that the eventual failure location would correspond with the "most active" geographic
sensor regions during the later part of the second hold forthe low burst vessels. However. this was not the case, as
there was no consistent correlation between the sensors
nearest the most probable failure location and the "mostactive" geographic sensor regions of AE generation during
the second hold, even for the lower burst vessels.

Based on the above discussion, a model might be described for the range of usefulness of the FR and its relationship to localized damage-based AE versus more uniformlygenerated AE occurring during the FR ramp. The model
also provides key explanations for the lack of perfect correspondence of the results for vessels C2 and 2-11 with theresults for the remaining vessels described above. For agiven set of vessels with a range of burst pressures (allproofed during the initial ramp to a fixed pressure level), theresults differ during the FR ramp in the following fashion.
Lower burst vessels are inherently proofed to a higher percentage of their failure strength than the higher burst vessels. As a result, the lower burst vessels are more likely tohave localized zones of more distinctive damage
61

Table 3 Summary of most active sensors vs. probable burst location.
Case (aCase (c)Case (b)Sensor # for
Sensor # of Most Approx.
Sensor#of 4
Sensor # of 4,.
,.
Rings Near the Active" Rings at
Pressure
Most Active
Most Active
Probable Burst
ofFR
Pressure of FR
Sensor Regions
Sensor Regions
Location: (listed Determination:
Deterduring FR Ramp
at End ofmination: at Previous Max.
determined near to far; bold
(bold # shows
Second Holdby visual# indicatesmatch with burst
Pressure (48.3(51.7 MPa;
inspection) nearest sensors)
location)
MPa' 7000 Dsi)
7500 DSi):° Latitude;
Polar ring;
Polar ring;
Polar sensors;
MPa
MPa
Polar sensors;
(psi)
(Dsi)
Eauator rinJ!
Eauator rinJ!
° Lomritude
Eauator sensors
Equator sensors
16,
15,
13,
14
16.
15,
14.
10
14
15.
16,
11,
14
15, 16, 14, 12
62.1
65°
S±
10°
Q
(2000)(9010)
7.8,6,52,8.6,5270° ± 300
2,5. 1, 6
1, 5. 6. 2
13, 11. 10. 12
1411, 16, 10, 14
11. 10 16. 12
62.9
65° S± 10° 13, 14. 16 15C2(2000)(9120)
5,8,6,7.
8, 4, 5, 6
4oo±30°5.8.6. 7
8,6.5.7
do not know
16. 15. 9, 132163.9
65° S± 10°
P
16. 12. 14. 13
15. 16. 12. 14(3000)(9270)
5, 1, 4.6
do not know?
6,5,8.7
6. 7. 1.5
14, 13. 10. 16
4164.2
65° N+ 10°
9. 12, 10. II
H
14. 16. 13. 12
16. 14, 13. 11(6000)(9310)
0° ± 300
4. 1.3.2
4. 1. 6 3
6.4.3, I
5.4.3.6
do not know
14 16 12. 10
35
16. 14, 13. 10
65°N± 10°67.0
B
12. 16. 10, 11(5000)(9715)?
do not know
5.6.7,8
5. 6. 7. 8
5.8.6. 7
13. 14. I I. 16
65° N+ 10°
35
I
68.4
9.12. 10. II
13. 14. 11. 12
11, 10. 14. 12(5000)(9915)
4.3. 1,2
330° ± 30°
8.6 1.5
8.6.5.2
6. 2. 8, .s.
12,9. II. 10
13. 15. 14. 16
46
IS. 10. II. 13
65°N± 100
69.2
2-11
IS. 10, 11, 16(6600)(10035)315°±45°
7. 1.5.6
1,5. 7. 6
6. 1, 5. 7
4.3. 1.2
9.13. 10. IS
43
16. 15,9. 10
74.0
65° N± 10° 13, 14. 16, 15
15. 16. 9. II
2-03(10730)(6300)
5 8 6,75 7.3, 8
300 ±30°
5.6.8, 73,5. 1, 8
16.11, 9.14
do not know
46
11, 10. 9, 15
65° S + 10°
74.9
S
11. 15. 16. 9(0870)(6600)
do not know
3.5.2,6?
2.3.5,6
1. 2. 3. 500 (on weld)
do not know
9. 10. IS. 14
4512, 11. 16. 14
76.0
11, 15.9. 10N(6500)(11020)2.3,4, 7
do not know
2,5,1.3?
5.2.3,646
16, II, 15. 12
16. 13. 11, 12
16, 11. 15.9
80.3
65° S± 10° 15,16, 14. 13
2-05(6600)(11650) 240°+ 30°
5,7. 8.4
8,2.7.3
7.6.8.5
8.5.7.2* "Most Active" defined as those regions haVing greatest cumulatlve sums of events; listed as most actlve to least active.
Longitude Angles: Degrees clockwise from filament winding feature when viewed from the North Pole.
VesselBurst
Pressure:
ID

Probable
Burst
Location(as

To discuss the lack of perfect correspondence of the daIain Table 3 with the above hypothesis [as well as to discuss
the scatter in the FRcorrelations with burst pressure in
Downs and Hamstad (1995»). a figure will be introduced
which shows the theoretical geometric attenuation due tospreading for a plate-like structure vs. the actual attenuationof lead breaks performed on a graphite/epoxy shell typestructure. The same sensor type and signal bandpass wereused for the experimental attenuation tests as for the actual
proof tests. Figure 10 shows the change in peak amplitude
as a function of propagation distance from a lead break on agraphite/epoxy cylindrical pressure vessel. The cylindricaldesign was easier to use for experimental purposes and also
allowed detennination of attenuation in two directions. i.e.•
axial and hoop. Clearly, significant amplitude is lost overthe first several centimeters of propagation. It is interesting
to note that the shape of the actual experimental attenuation
curve matches quite closely with the attenuation that is predicted by the theoretical spreading (i.e., geometric attenua-tion governed by lI..Jr for a plate-like structure), particularly
at shorter distances. These curves predict that when an AE
source event occurs directly underneath the center of asensor. a loss in peak amplitude on the order of 24-30 <B
occurs by the time it is sensed at a second sensor only 65
mm away. For the vessels C2 and 2-11. Figs. II and 12
show the amplitude distribution for events that only hit one
sensor. Since. in most cases the next closest sensor was at
most only 65 mm away, the maximum difference between
the greatest peak amplitude in these figures and thethreshold (48 dB) should be about 24-30 dB. Clearly, the.experimental data are consistent with this prediction. More
importantly. these geometric attenuation curves in Fig. 10
predict significant numbers of seemingly significant amplitude events that will only be sensed by the single nearest
sensor. Examination of Figs. II and 12 shows that thistypically is the case. Figure 13. which shows a distributionof the number of sensors hit by each event during the FR
ramp for vessels C2 and 2-11. is typical for many of the

-

C:)

~

20

~
.~
C.

10

~

0

~

-10

C

-20

-Theoretical Attenuation (1/--Ir)~ Actual Hoop Attenuation-0-Actual Axial Attenuation

fo
]

-30

U

Note:
The peak amplitude value at a
distance of 0 rom shown by b(i.e., at the center of thesensor) was provided from alead break performed on thecenter of the epoxy wear-plateof the sensor.

+-"'T""...,...-.-....,.._..,._..,......,.-.,.---.--.............

o50 100 150 200 250
Distance From Leadbreak (mm)Fig. 10 Change in lead break peak amplitude as a function of propagation distance on a cylindrical graphite/epoxy pressure
vessel. The experimental and theoretical amplitudes were nonnalized to 0 dB at a distance of 6 mm away from the center ofthe sensor face.
I~ Threshold (48 dB)

,,
,,
,
,

600
CO C
.5 ~ 500

> 0

=-c
:ern
u
u:l

_"0

C

Vessel C2:
Information shown is only
for those events which had atotal of one hit in the event

~N

~~

I

400

='

~l-

~=
t1Jo.

~oo

... e 300

N

0<

.-- =
u 200
~~

~c..

=' u
0'-::

100

0
45

50

55

60

65
70
75
Corrected Peak Amplitude (dB)

80

85

90

95

Fig. 11 Corrected peak amplitude distribution for Vessel C2 for those events having a total of one hit in the event; data forsecond (FR) ramp of Profile (A) up to 48.3 MPa (7000 psi).

CO C
C ~

~Threshold (48 dB)

50

I ~~

'> ~
:i!rn
u

40

='

30

I

~iP,

u:l

_"0

C

~=
UJo.

~~

_

...0 <e 20

Vessel 2-11:
I
Information shown is only for I
I
those events which had a total I 24 - 30 dB I
of one hit in the event.
: above :~I Threshold I

O\N

,....

.~~

-ac..
u
u
C/-c

=

10

- 0

v~

45

50

55

o

N

-0000

~,

,
I

I
,

I
I

I
I
-0000

60
65
70
75
Corrected Peak Amplitude (dB)80

Fig. 12 Corrected peak amplitude distribution for Vessel 2-11 for those events having a total of one hit in the event; data forsecond (FR) ramp of Profile (A) up to 48.3 MPa (7000 psi).

13 (a)500

Vessel C2

400

500 .,.-~13~(b"'_)400

Vessel 2-11

300
200

300

100

100

--,

200

o 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16
Total Quantity of Hits in Each Evento

2 3 4 5 6 7 8 9 10 1 I 12 13 14 15 16
Total Quantity of Hits in Each Event

Fig. 13 Distribution of quantity of hits in each event; data for second (FR) ramp of Profile (A) up to 48.3 MPa (7000 psi):a) Vessel C2; b) Vessel 2-11.

~~

c .,g

200,-------------------.

'>= ISO
:c :c
.-=:
CI)

<I)

<I)

'5 '0 100

~·z
o :;

50

>.=
.-=:
0

0

e==

=O~

Vessel C2:
Data only to 14.4 MPa (2100 psi) duringfsecond (FR) ramp 0 Profile (A), Le., thepressure at which FR was detennined.

2 3 4 5 6 7 8 9 10 II 12 13 14 15 16
Total Quantity of Hits in Each Event

Fig. 14 Distribution of quantity of hits in each event for Vessel C2; data for second (FR) ramp up to 14.4 MPa (2100 psi) .
vessels. Clearly, the dominant characteristic is for mostevents to hit only one sensor, i.e., the nearest sensor.
Additionally, as Fig. 14 shows, this characteristic is present
even when considering only the initial ponion of the FR
ramp (i.e., up to the pressures at which the FR Wa<idetennined).

presumably occurred for vessel C2). But, if the distinctlydamaged zone is farther away from the nearest sensor, thenthe "first hits" recorded by that nearest sensor will tend to bequantitatively dominated by the uniformly-generated AEfrom the immediate vicinity around this sensor (as presumably occurred for vessel 2-11 and possibly vessel I).
Thus, the quantity and type (Le., uniformly-generated or
localized damage-based) of "first hits" recorded by thissensor will not be distinguishably different from thoserecorded by the other sensors on the pan. In this latter case,AE from proof tests can only be expected to correlate withthe general quality of the composite material rather thanwith the localized, distinctly damaged zones that lead to
failure. To improve this situation (when the precise locationof the failure controlling zone is not known prior to theproof test) would require accurate source location of AE
events. Then, with a sufficiently low threshold. at least
three sensors would be hit by a significant quantity of theevents recorded. In this way, one could pinpoint the locationof the localized, distinctly-damaged zone on a smaller, more
precise scale than merely being able to identify the "mostactive" geographic sensor regions used in this analysis.

The above perspective has several implications for thecurrent technique of selectively using "first hit" data fromthe single "most active" geographic sensor region during the
FR ramp to correlate with burst pressures, as presented by
Downs and Hamstad (1995). The physical size of the
failure-controlling (Le., more-distinctly-damaged) zone within the vessel is likely much smaller than the geographic
sensor regions (depicted in Fig. 5). Thus, whether or not
the AE arising specifically from this localized distinctlydamaged zone will have a significant or dominant influenceon the overall "first hit" data recorded by the nearest sensor
wiU depend on the physical distance between the localized
failure-controlling damaged zone and the nearest sensor. If
the distinctly-damaged zone is sufficiently close to the nearest sensor, then the AE specifically originating from thedamaged zone could predominate over uniformly-generated
AE events occurring within the same geographic sensor
region. This increased AE activity from the distinctlydamaged zone also could significantly increase the total
number of events occurring in that panicular geographic
sensor region versus other sensor regions on the pan (a<iSuch accurate location capability requires a waveformbased AE system with sufficient speed to recotd wavefonn
information at a sufficiently high rate. Specifically, it isdesirable to have equipment which will gather a length ofwaveform information and then be able to store that infor64

mation within about 500 tls on each and every channel,
regardless of the number of channels being used and thedegree of AE activity on the channels. It is important thatthe time required for storing a waveform be brief because
during the storage process the AE system is unable togather or record new incoming information. Since the vast
majority of events measured and recorded will still only hit
one sensor. it will be necessary to gather and record a large
amount of data to ensure that an adequate quantity of data isrecorded which hit at least three sensors to allow source
location analysis. Therefore, the waveform-based equipment
must accommodate a high rate of incoming data, and thiscan only be successfully achieved with a fast turnaround fordata storage. With waveform-based AE equipment (vs.
parameter-based. traditional equipment), it is expected thatscatter in correlations of FR with burst pressure could be
reduced further still (especially for higher burst vessels), andthe analysis required to develop the correlations would beeasier.

measured if the middle of the sensor apenure were directly
above an AE source event. Thus, to rephrase the case whenall 16 sensors are hit. this situation occurs when the "sensor
source magnitude" is equal to or greater than a certain
amplitude. One may note that at first glance Figure 13a(for vessel C2) does not appear to strictly follow this logic
since it has an interesting peak at 14 hits per event. rather
than at 16 hits per event. This can most likely be explainedby the substantial material attenuation in vessel C2. asevidenced by the fact that during the second ramp and second
hold, each event for this vessel had 2.3 and 3.6 hits on
average, respectively. Thus, AE source events in vessel C2
were less often able to hit all 16 sensors due to the material
attenuation. This peak (at 14 hits per event) could haveappeared at a different point in the distribution had thematerial attenuation or density of sensor placement beendifferent.

With the perspective developed above, Figs. 13a and13b offer additional understanding of the effects of wave propagation on the local variations in AE sensed in a sphericalcomposite pressure vessel. First, the large fall-off fromsingle-hit events to two-hit events (on the order of a factorof 10 to 15 : 1) is due to JI.,Jr geometric spreading attenuation. Second, the fall-off in terms of the quantity of sensors
hit per event from 2 to 8 is due to both material attenuationand lI.,Jr spreading. Third, the increase in quantity of sensors hit per event from 9 to 15 is due to the spherical shapeof the test articles. Since the sensors furthest from the AE
source event receive acoustic wave packets from two directions at approximately the same time (because of the spherical shape of the vessel), these waves superimpose on eachother to result in a greater measured and recorded amplitude
than would otherwise be warranted by the propagation distance. This "superposition-enhanced" amplitude exceeds thethreshold more often than the amplitudes of the individual
waves would ordinarily have. and thus a greater number of
sensors are hit.

1. Because of geometric attenuation due to spreading,

5. Conclusions

most AE hits recorded from a well-designed graphite!
epoxy pressure vessel originate within the immediate,
localized vicinity of the sensor recording the hit. This
localized vicinity is substantially smaller than the "firsthit" geographic region surrounding the sensor.

The sensors nearer to the source event also receive two
wave packets, but the packets are spread out in time. Thus,
the wave packet superposition does not result in significant
increases in the measured and recorded amplitudes in such a
way that a greater number of sensors are hit than if thesuperposition had not occurred. Founh, the second mostprevalent event (as shown in Fig. 13b for vessel 2-11) is
one that hits all 16 sensors. The reason for the extra
increase in quantities of events having 16 hits (vs. whatmight be expected due to the superposition of wave packets
coming from two directions) is that once an AE source
reaches a cenain magnitude, then all other sources of thatmagnitude or greater always hit all 16 sensors. To characterize this cenain source event magnitude, we introduce a
concept called the "sensor source magnitude." This "sensor
source magnitude" is the peak amplitude that would be
65

2.

The "first hit" geographic sensor regions used in theanalysis presented here are substantially larger inphysical size than any localized, failure-controllingzone which may produce damage-based AE. Thus, it isdifficult to correlate the "most active" geographic
sensor region with the eventual failure location unless
one or both of the following are true: a) the previous
maximum pressure prior to the FR ramp was highenough relative to the eventual failure pressure; and/or,b) the localized zone of the vessel controlling the burst
strength is located sufficiently near (or directly below)
the sensor within the "most active" geographic region.

3.

Use of a waveform-based AE system with high speed
processing capability should improve the ability todetect localized zones of damage concentration, and tocorrelate the AE from that localized zone with bothburst pressure and eventual failure location.

4.

Successful correlations of the Felicity ratio (FR) am
burst pressure for those vessels which were not proofed
to a significant fraction of the ultimate burst strength
prior to the FR ramp are probably due to the FR being
related to the overall quality of the composite material
as fabricated, rather than being related to localized zones
ofdamage.

Acknowledgments
The authors thank Jamisen Jensen and Robert Lauerothof Brunswick Composites for their attention to detail in theperformance of the proof pressure tests, Dave Sheahan of
Lockheed Martin for his innovative test fixture design,
Mack Roberts of Lockheed Martin for his assistance withthe design-of-experiment results, and Lawrence Loechel of
Lockheed Martin and Vincent Johnson of WPAFB for theiron-going suppon of the Composite Overwrapped Pressure
Vessel Task 6 program. The effon described herein wassponsored by the fonowing agency: Manufacturing Technology Directorate, Wright Laboratory, Air Force MaterielCommand (ASC), United States Air Force, WrightPatterson AFB, Ohio 45433-6533.

References
K.S. Downs and M.A. Hamstad (1995), "Correlation of
Acoustic Emission Felicity Ratios and Hold-Based Rate
Moments with Burst Strengths of Spherical GraphitelEpoxy
Pressure Vessels," 1. Acoustic Emission, 13(3/4), 44-54(in this issue).
R.L. Moore, M.A. Hamstad, and T.T. Chiao (1974),"Stress-Rupture Behavior of Graphite FiberlEpoxy Strands,
Composite Materials and Structures, 3(1), 19-23.

A Study of Acoustic Emission-Rate Behavior in Glass
Fiber-Reinforced Plastics
A. J. Brunner, R. Nordstrom and P. Fliieler
Abstract
This study examines acoustic emiSSion (AE) rate
behavior of specific glass fiber-reinforced plastics (GFRP)
systems under static and stair-step loading. Coupons ofglass fiber (GF)-polyester and GF-epoxy are taken to failure
under static tensile loading. The AE-rate behavior is
examined under ranges of temperature (-50°C to 140°C)
and strain rates (O.OI-IO%/min). The AE behavior understair-step load is studied for comparison. For stair-step load
programs, specimens of different types (test coupons,square profile tubes. GFRP-foam sandwich shell) andscales (overall length between 210 and 5500 mm) are tested
with varying loading direction: test coupons under tension.
filament wound tubes under torsion and the sandwich shellunder compression.
In static tensile tests, glass fiber reinforced epoxy andpolyester respond with exponential AE-rate behavior, i. e.,
AE = kent. Determining the exponential factor a for eachmaterial by superimposing the rate (differential) and cumulative AE curve is found to be simultaneously a convincing
method for establishing exponential behavior and efficientquantitative analysis. The exponential factor a was foundto be a function of strain rate and invariant within a certain
temperature range. In stair-step tests, cumulative AE
curves were compared at different scales and found to be
similar in shape at all scales.

1. Introduction
The patterns of AE generated for a specific stair-steploading program during hold and reload periods when
defects are present have been exploited in field test procedures (CARP, 1981) for diagnosing structural integrity
successfully (Fowler, 1986; Fowler et aI., 1989a, 1989b,
1992). Hamstad (1992) has reviewed hundreds of papers
citing eight goals sought in AE criteria evaluation foradvanced fiber composites. In the area of damage history,each case of evaluation is unique, representing evaluation
criteria for correlating AE to a specific damage monitored.
Received 9 October 1995. The authors are affiliated with EMPA
(Swiss Federal Laboratories for Materials Testing and Research),
CH-8600 DUbendorf, Switzerland. This paper is based on two
separate papers presented at the Fifth International Symposium on
Acoustic Emission from Composites. AECM-5. by Brunner et al.
(J 995) and by Nordstrom and Brunner ( 1995).
Journal or Acoustic Emission
Volume 13. Number 3/4

Correlation between distinct AE features and specificdamage is often used as goal of AE analysis. Might there
also be similarities in AE patterns within classes ofmaterials such as GFRP that can be found with empiricalcorrelation? Staning with an exploration of qualitative
similarities observed in the AE-rate behavior of GFRP
tensile coupons, GFRP materials and structures are further
explored under different loading conditions.
The staning point is the exponential increase of AE
cumulative or AE-rate curves. This behavior has been
observed in a wide range of materials and for different
types of loading. The CARP procedure, for instance, uses a
rapidly (exponentially) increasing count rate in glass fiberreinforced plastic (GFRP) tanks as test termination criterion(CARP. 1981). An exponential rise in the AE-rate versus
time of rocks under triaxial deformation (Sammonds et at.,1995) and an exponentia1Jy increasing cumulative AE
energy curve versus load (four-point bending) of a SiCfiber-reinforced Ti alloy (Takashima et aI., 1995) can becited as examples from recent publications. There havebeen attempts at correlating the typica1Jy exponential
cumulative AE curves with physical phenomena anddamage accumulation (Awerbuch, 1988). An earlier publication (Brunner et aI., 1994) reponed on a series of experiments on tensile specimens made from polyester with two
types of glass-fiber reinforcement: continuous unidirectional (UD) fibers and three layers of 0°/90° combined matwith two chopped strand mats in-between. The UD fiber
reinforced material is labelled "A", the chopped strand matmaterial "B". The findings of this study are summarized
below. Further test results on these materials are presented
here.
For materials A and B, the AE signal rate and thecumulative AE curve can be described by an exponentialfunction. This AE behavior is most easily shown as asuperposition of AE-rate and AE cumulative curves. The
exponential function is confirmed as the rate of AE is
proponional to the cumulative AE. This property can be
expressed as:
AEcumulative = keal
which implies
AErate = k ex eat.
The superposition of the cumulative and of the rate curve
wiIJ have the same shape, provided that rate steps are
sufficiently small to approximate a differentiation of the
0730-0050195/SS.00I13067.(fl7Copyright@1995 Acoustic Emission Groupcumulative curve function (i. e.• rate time « total test time).
This behavior will be caUed "two-parameter model" in meremainder of the paper. Three AE signal parameters(counts. hits, rms-energy) have been used for the rate
analysis. AE counts yielded better agreement than hits or
nns-energy.

Square hollow profile GFRP tubes were tested underangular control of a stair-step torsional loading sequence.
The system is an E-glass fiber-reinforced vinyl-ester with40 volume % glass with roughly 60% of the fibers in thecircumferential direction. The specimens were 500 mm
long and 5 I mm wide. The profile wall thickness was
between 3 and 4 mm comprising a total cross-sectional areaof about 750 mm2 • The square profile had been previously
loaded up to 1° in torsion.

The exponential factor a from the two-parameter modelis 0.010 sec-I for material A and 0.020 sec· 1 for material B.
BoIh experimenlally obtained curves (rate and cumulative)
are identical if the scale of the AE rate curve is multiplied
by a factor of 1/0.. Funher. a data fit with me exponentialfunction eal was performed on the curves to check on this.
The value of 0. did not change within a material specifictemperatUre range.

A 5.5 m tall structure. a three-layer GFRP-foamsandwich shell was loaded in axial compression. Figure 1
shows a schematic of the shell. The shell had a hollow
cross-section of approximately 2.7 x 2.9 meters. Each sideof the shell had large cut-outs. In the largest cut-out
regions GFRP reinforcement plies were placed perpendicularly in the sandwich material.

Deviations from the exponential behavior have been
observed at both high and low temperatures. At high temperatures (above +120°C for material A. above +100°C formaterial B) a second exponential that is increasing fasterwith time, i.e.• with a larger exponential factor. appears. At
lower temperatures (+60 oC for material A. room-temperature for B) a sum of a linear and an exponential function Klin t + KeltP eat describes the cumulative AE curves
better than a simple exponential.

5.5m

AE Sensor
PositionIn the farst experiments of the present paper, the AE
behavior of glass fiber-reinforced epoxy (material C) isinvestigated under static tensile loading until failure. All
materials (A, B. and C) are also investigated under different
load rates and with different gripping arrangements than in
the previous publication (Brunner et at. 1994). In a second
series of tests. static tensile loading has been replaced bystair-step loading in different loading directions (tensile.
torsion and compression). The AE during hold periods andAE during reloads including the loading immediately
following the reload are investigated in glass fiberreinforced epoxy (material C). filament wound glass fiberreinforced epoxy tubes or in a GFRP-foam sandwich shellstructure. i.e., on scales varying from 210 to 5500 mm.

Fig. 1 Sketch of shell structure

2.2 Loading Programs

Five types of specimens (materials or structures) are
reported on in this paper. Table 1 summarizes material
properties pertinent to each test

The initial test conditions served as reference conditions for all funher tests with static tensile loading. These
reference conditions are +23°C (50% relative humidity) and
1.0 mm/min constant crosshead speed until failure. The
reference conditions were used on materials A. B and C for
specimens without tabs and clamped with wedge grips.
The tests beyond the reference conditions were a varianceof one parameter at a time: temperature. crosshead-speed(strain rate). and loading program. When the stair-steploading program was used. the specimen size and corresponding loading rate were also altered.

A glass-fiber reinforced epoxy (labeled material "C")was used for tension testing here. Additional testing (strain
rate and stair-step) on the glass-fiber reinforced polyestermaterials A and B is perfonned. Specimens from materials
A. B. and C have been cut to a nominal length of 210 mm
and 20 mm width from rods with a nominal thickness of 4mm. The gage length was 120 ±S mm.

The test temperature has been varied in the range from_20° to +120°C. Three epoxy specimens (material C) were
tested at temperatures outside this range (-50°, _30° and+140°C). Cooling and heating produced tensile or compressive loads due to thermal contraction and expansion.
respectively. The reaction loads from heating or coolingwere less than 10% of the failure load at extreme

2. Experimental Setup

2.1 Test Specimens

68Table I Material data (determined at EMPA)
Composite A
MatrixFiber Content
LayersFiber orientation in Layers

Center layer I Core

Matrix Glass-Transition
TemperatureDensity
Scale Oargest "free"dimension in loadini! fixture)

Composite B

Polyester
Polyester38±2 vol.%18 + 2 vol.%3
3
Continuous UD if 0°/90° combined
center layermatCompositeC
Eooxy
47 + I vol.%24
0°/90° woven
rovingSquare Profile
Tube
Polyester
40 vol.%NA
60% incircumferential
direction

Sandwich Shell
PolyesterNA
3
Wound fromcontinuous UD-

Chopped strand
mat

-

-

- 1l0° C

-90°C

NA

NA

2 foam cores,
total
70mm thickNA

1.62 Mglm 3

1.57 - 1.65
M2Im 3210mm

1.86 Mglm 3

NA

NA

210mm

360mm

5500mm210mm

temperatures and less than 5% for the other tests. At roomtemperature (+23°C) the cross-head speed has been variedin the range between 0.1 and 10 mm/min in order toinvestigate the strain rate dependence. At room-temperature, tests with hydraulic grips (40 bar pressure) at different
cross-head speeds have been performed for comparison
with the wedge grips used in the standard test procedure.
This loading program is seen in a typical curve forglass fiber-reinforced epoxy (material C) in the upper left ofFig. 2. The ultimate tensile strength (UTS). the strain to
failure, and the (tangent) E-modulus that are obtained fromthe curve are indicated. The corresponding AE behavior isshown as well.
The stair-step loading program for the tensile tests isshown in Fig. 2 (upper right). The specimens were loadedwith a constant displacement rate of 1.0 mm/min. A time
period per load cycle was chosen for each specimen. Hold
periods lasted for a minimum of two minutes or until the
AE rate for events > 55 dB was less than 5 hits in two
minutes. The load program began with two cycles comprising a load increment and a hold period of one minute
minimum. The third cycle comprised a load increment, ahold period minimum of 4 minutes. an unload period equal(in time) to the load increment and a one minute hold at thedecreased load. After the third cycle, a reload interval
equal to the load time increment is included. Cycling
continued upward until failure.
The loading program for the torsion tests is shown in
Fig. 2 (lower left). The tube was loaded, held at constanttorsion angle and then completely unloaded during eachcycle. The loading rate was 2.00 /min for each load cycle.
The hold periods following the load increment had aminimum duration of one minute for the earliest cycles. but
this was extended as acoustic emission continued longer
into the hold period. The maximum angle on the first threecycles was 1.5°, 3°,4° and then was increased by 0.5° on
every cycle thereafter. The final load cycle was 12°. which
was repeated twice without increase (21 load cycles total).
After this loading program, there was significant visuallydetectable delamination and matrix cracking, but there wasno ultimate failure.
The shell structure was loaded three times undercompression to 300 kN, once to via a stair-step program
and twice by completely loading and unloading without
hold. The structure was finally taken to failure at almost
600 kN. The loading curve for the shell is shown in Fig. 2.
lower right.

2.3 Test Equipment and Preparation
The specimens of material A. B, and C were loaded ona servo-hydraulic universal testing machine. Loads were
measured with a 200 kN load cell and strains recorded witha mechanical extensometer (gage length 50 mm). One
sensor was placed in the center of the gage length for all
tensile specimens and one additional sensor on each grip.
For tests above or below room-temperature atemperature chamber was added to the test configuration.
The temperature was recorded by a thermocouple inside thechamber. Cooling to -20°C took up to 30 minutes whileheating to SO°C took up to 80 minutes. Cooling to -50°C
was somewhat slower, taking 3 hours. All specimens were
kept at the test temperature for one hour before loading. An
additional, free-standing sensor was monitored inside thetemperature chamber.

Strain to Failure

0.50Strain [%)1.

Time [min]
1.5

2-

900

400

800

'iii'
n..

300

700
600

m

200

~

»
m
~

~

100

!
200

(1)100

0

100
0

::J

a
7
CD

J:
c
o

'Pi
~

6
5
4
3
2

n

1000

350

»m

300

~

£

5)

0

1000

40

n
n n

J
2000

400

2000

3000

4000

Time [5)

h 150

3000

.~ II

,~

10

Time [min]
15
2)

3J

350

800

»

300

100 ii)

z250

700
600

5OOii)a:0 200

400

"§

5)3

.9150
100

300

a

»
m
~

!-

~J

5

400 0

;

1\

o nl 1. •

70

0

0

1

m

m

200 250 30D 350 400

3J

50

~15O

Time [min)1040!a250 (l)200 '0
0
C
150 a
100

Time [5]O3Jn.. 250

~
(/)
200
(/)

m 100 150

3)

III

'0
0

400
300

10

0

350
_300

c

500

~

en

400

0

c

{I!.

200 .!!!.
100

m

o

0

4000

m

;

250 500

750 1000 1250 1500 1750 2000

Time [s)Time [5]Fig. 2 Load programs of tests. Above: GF-epoxy (material C) tensile coupons. Left: stress-strain curve for static tensile test
at 0° C. Loading rate: I mm/min. Right: 9 of 10 cycles of stairstep loading. Loading rate: 0.06 %/min. Below: Structural
tests under stairstep loading. Left: first 10 (of 20) cycles of square profile tube in torsion. Loading rate: 2°/min. Right: first
4 (of 12) cycles of shell in compression. Loading rate: 0.5-1.0 kN/s.

The torsion test on a servo-hydraulic universal testingmachine was monitored with four sensors, two near theupper grips and two near the lower grips. Ten sensors werespread around the shell for the compression test. The load
was applied by hydraulic actuators. Each sensor wasplaced near one of the cut-out regions. Some of the sensor
positions on the shell can be seen in Fig. I.

to 1.4 ms. Load, strain, and temperature have been recorded together with the AE signals.

3. Results
3. / AE Behavior under Reference Conditions
Three AE signal parameters (counts, hits, rms-energy
per hit) have been used for the analysis. It is found that theAE signal rate and the cumulative AE curve for all threeparameters for material C can be well described by an
exponential function. The same exponential factor a10.014 sec· (with an error estimated to be between 5 and10%) is calculated from the superposition of the cumulativeand of the rate curves for all three AE parameters for testingat 1 mm/min. Figure 3 shows plots for tests at room
temperature and 80°C (discussed in Sec. 3.2). The figure
shows AE hits, AE counts. and AE rms-energy per hit, both
cumulative and rate curve of each parameter superimposedwith a least-square fit of the cumulative curve.

A digital AE recording system (AMS-3 from Vallen
Systems) with 150 kHz resonant piezoelectric sensors(Dunegan Engineering) has been used. A temperatureresistant vacuum grease has been applied as coupling agent.
AE signals (standard parameter set with the energy parameter chosen as nns-energy) have been recorded throughout the tests, including heating and cooling. The AE
acquisition settings used were: threshold 55 dB for tensile
specimens and torsion tubes and 41 dB for the shell (inreference to 0 dB = I I!V at the preamplifier input), 34 dB
gain. and 3.2 ms rearm time. For the static tensile tests withhydraulic grips. the threshold for the guard sensor on thelower grip was 65 dB (ref. 0 dB I I!V). The threshold on
the control sensor in the temperature chamber had been set
to 35 dB in the previous tests of materials A and B. For thehigh-rate tests at > 1 mm/min the rearm time was reduced==

The mechanical behavior of the three materials in static
tension is shown in Table 2.

70

230C

~ 0i-_ _0;:.;.;;..5_ _---:.;1.~--1;.;;.5;;...._

5"

-

o 2S
....

_.

~2)

40 0i-_ _--.;0;.;;.5;;....---1.;.;..----.~1;;;;.5.".6oo___i"2.35O_

AE count rate
accumulated AE rdc
data fit

....

300
250

~

2S

-E 15
8W 10

200
100

~

<

Strain [%]Strain [%]

~

o

0
~

AE count rate
accumulated AE counts
data fit

-

8

~

>.

21

_.

AE energy rate
accumulated AE ene
data fit~-.~...

ED
40

W

<

15
12.5
10
U
5

8)

Ifi 4
2

2)
~

__

o

100 150 200 250 300 350 400

100 100 200 250 300 350 400

-

8

'6

.... 6

AE hit rate
accumulated AE hits•-

data fit

~

40

~ 2

~

~

~

O_......

0.5
_
_.

~

x

1.5

1.

AE hit rate

220

:I:
;:::;:

8
6

100

4

ED

-....

2

~
-.J ~

1~
8)

~

100 150 200 250 300 350 400

»
m

200
180
160
140

accumulated AE hits
data fito L.MIlI!!YIi~~~r=:_---_---I 19

&l

(l)

40
0
100 150 200 200 300 350 400

o
14
12
10

8)

:f 4

~
::D

Time [s]

100
~

ED

00
160

gt

Strain [%]1:.:;.5;;...._---:;2.120
110

~

m

8)

~

»

80
40

AE energy rate
accumulated AE energy
data fit

Time [s]Strain [%]
-

o

1~

2.5

o

10 0r--_......:O;,:;:.5;...._......:1;,...

~j2)0i--_ _--.;0;.;;.5;;....---1.;.;..----.~1~.5
17.5

100

6

c:

a

Time [s]Strain [%]

2.
120

CD

»
m
oo
::D

~ 1..-....1Id~~

100 100 200 250 300 350 400

10 0i--......:0;,:;:.5;....-......:1:.;..._ _,.1r-.5~

00

15
10

Time [s]Strain [%]
cD'
o
....

00

2)

100

5

--

::D

~

~

100 150 200 250 300 300 400

Time [s]Time [s]Fig. 3 Cumulative and rate curves for 3 AE parameters at two temperatures for GF-epoxy. Curves are from tests at 23° C(left) and 80° C (right). AE parameters are hits (top), counts (center) and AE energy (bottom). Specimens tested with aconstant cross-head rate of 1 mm/min. The fit shown (dashed) is an exponential function with an exponential factor a
0.014 s·l.

=

Table 2 Static tensile test results

SystemUltimate Tensile Strength(+23°C)
E-modulus (tensile, +23°C)
Strain to Failure (+23°C)
EXDonential Factor

Composite A
Glass I Polyester (UniDirectional)
400-500MPa(parallel to fibers)
28GPa
1.5 - 2.0 %O.OlOs·1

71Composite B
Glass I Polyester(combined mat)
80·140MPa

CompositeC
Glass I Epoxy(ravine)400-450MPa

SGPa
1.4 - 1.6 %0.0205'1

20-25 GPa
1.9 - 2.4 %0.0145"

Fig. 4 Photographs of one GF-epoxy specimen (material C). Specimen tested to tensile failure. Ultimate failure is seen in(top) shear break and (boltom) transverse break (from back). The most probable delamination path sequence begins at theshear break and ends at the transverse break.
During the tests no visually detectable signs of damage
have been observed in the specimens up to failure. Posttest visual inspection showed that failures mostly consistedof a delamination along an inter-ply plane, with shear
breaks on one side and transverse (lateral) breaks (sometimes in the grip section) on the other side (Fig. 4).

curs about 150 s after the start of the test. A significant
number of large amplitude hits occurred after the first 1SO

s.
The UTS decreases linearly with increasing temperature for all three materials. A linear decrease with increasing temperature has also been observed for the strain to
failure. The two types of grips (wedge and hydraulic)yielded the same values for the UTS for identical strain rate(cross-head speed of I mm/min). At failure materials C andB unloaded immediately. For material A the load drop at
failure was much less (typically 20 - 30% of UTS). The(tangent) E-modulus of material C determined from theinitial slope of the stress-strain curves (tensile test) isaround 22 GPa. except at temperatures below roomtemperature where it is increasing to 26 GPa. An analogous
increase has been observed for materials A and B.

3.2 Static Tensile Test AE Behavior over a Range of
Temperature
The AE behavior, especially the observed fit of one
exponential factor, remains constant for all test temperatures up to and including +140°C and down to temperatures of -30°C. A transition to a different behavior occurs
at this temperature. In some tests at different temperatures
the AE rate is dropping off from the exponential increase in
the last 50 s of the test (Fig. 3). In most tests no hits withamplitudes greater than 80 dB (ref. 0 dB = I J.lV) are
observed before failure. The sensors on the grips recorded
few AE signals (hits) except in the last 5 s before failure.
At failure, the amplitudes of these hits exceeded thoserecorded by the sensor in the center of the specimen. The
cause of the decrease of the AE rate towards the end ofsome tests remains unclear. If observed, it occurs within
the last 50 s before failure and no trend with temperature
has been observed. Two possible causes are consideredhere. The low AE hit-rates exclude saturation of the AE
system as a cause. Damage accumulation, however, mayinterfere with signal propagation and reduce signal detectability.

3.3 Static Test Results over a Range ofStrain Rates
The exponential factor determined from the twoparameter model is independent of temperature but depends
on the strain rate. Figure 5 shows the exponential factors
for material C from the fit at room-temperature taken at
different cross-head speeds. The exponential factor varies
between 0.0030 s'( and 0.20 s·J and depends linearly on the
cross-head speed.
The linear correlation between exponential factor andstrain rate is particularly interesting (Fig. 5). It is cautionedthat at the fastest rates, deviation from this slope are notwell represented on this scale. The dependence of the UTS
on strain rate (cross-head speed) has been investigated atroom-temperature. The UTS remains roughly constant in

At -50°C, the behavior is clearly different. The cumulative AE versus time rather behaves like two linear regimes with different slope, the onset of the second slope oc72

Glass Fiber/Epoxy (C)0.2-r---------------------..,

-....

o

Exponential Factor «x)

J,...!!
a-

So
CD

..

II. 0.1

'ii
c
CD
c
o

CL

><

W

0.0 -f'I--r----r-.....--,-~--r----__r-""""I""-..,.____,r___1

o

1

2

3

4

5

6

Strain Rate [%/mln]
Fig. 5 Strain rate dependence of the exponential factor «x) for GF-epoxy. Values of a for material C determined from thesuperposition of the AE signal rate and the cumulative AE curves versus cross-head speed (strain-rate) at +23 0 C. The linear
dependence on the strain-rate is shown by a least-square linear fit.
the range between 1 and 10 mm/min and tends to decreaseat lower cross-head speeds (by about 15% at 0.1 mm/min).

cycle when the load was quite low compared to the failureload or in a hold period when the AE was typically muchsmaller, it is particularly noticeable. The AE acitivity thendecreased to a lower rate of emission.

3.4 Stair-step Loading Programs and Different Scales
In the tensile tests, the number of cycles until failure
largely dependent on the size of the load increment per step,was between 7 and 17. Rarely was damage visible before
failure. The structural element tests (torsion) comprised
more than 10 cycles and visible damage was noted wellbefore failure. There was also readily identifiable AE
bursts which were localized in time (e.g., Fig. 6, bottom
right). This effect will be called a "local burst" whenreferenced in the rest of this paper. The AE generally
increased with each period of increasing load for all tests
and each hold period preceding an increase in hold, except
for the local burst. In all cases tested in the stair-step,tensile specimens, structural elements and structure, there
were some bursts of emissions that did not follow thegeneral monotonically progressing AE accumulation.
Toward the end of the failure cycle, these bursts could also
be correlated to drops in load or even visible damage. In
the sandwich structure, the visible damage was detected
well after the local bursts in the AE activity and wasobserved in the vicinity of the most active AE sensors.

The AE from stair-step loading is separated into holdperiods and reload-new load periods. Selected cycles are
scaled and superimposed in Fig. 6 for both periods. The
load cycles represent a range of cycles where the quantityof AE is statistical1y significant (the later load periods). In
early stages of the stair-step cycle, the emissions aredetected mostly during the load cycles. For tensile specimens, the AE activity during hold cycles is always greaterthan the activity during loading cycles starting at 70% of
ultimate load. This ratio of activity per hold to activity perload climbs consistently with increasing load cycle. By the
final load cycle, the ratio of hold activity to load activity
was about 3: I for the tensile specimens (as measured by AEhits).
The shape of the accumulation looks similar but thescale increases on subsequent loading cycles. The AE that
occurs in reload periods was greatly reduced in tensile
specimens when the previous hold period was maintained
until the AE disappeared. The tensile specimens broke
mostly in hold periods in these tests, in two cases after
more than 3 hours of steady emissions. In one of these
specimens, there was no emission in any reload cycle.
However, the hold period required to diminish AE to zero
was significantly longer than four minutes after the fourth
cycle.

With each material there was at least one period,
representing less than a full cycle, where a local burst
significantly increased the AE rate but was not sustained.
The local burst was noticeable in the rate curve and usuallycontinued at least five seconds and sometimes more than
one minute. If the local burst increase occurred in an early
7J

Hold Period

Reload·Load Period--------Tensile Test~_ ..... --".- ...
8000

Tensile Test€,3500.g(1) 3000

hits
hits cycle 5 (x 80)
hits cycle 7 (x 6)hits cycle 9~ 2500~ 2000II)..
10000 .,.
6000

hilS
hits cycle 5 (x 200)
hits cycle 7 (x 7)hits cycle 9~ 1500.':: E 1000... relpad

::c~

u

~.e 500 l

.

o

20

I

LaP'-

40

60

80

100

O·

,
100

120

200

300

400

Time [5]Tube under Torsion
700€' 350hits
hits cycle 11 (x 8)(1)
a.. 250 -- hits cycle 13 (x 4).1:- - hits cycle 15"'0 200(1).g 300 -

•

400
300

11)"'5::::E 100
::c~

w~
<t:_

.- ----- .. - .• - -_.

o

50

..#

-,,"

0' , , . , . , , I

100

.

50

100 150 200 250 300 350

100 150 200 250 300 350 400
Time (5]Time [s)Shell under Compression
1000
=0
o

'iii 800 -

a..

5000t

h'tIS

- - hits cycle 3.1: 600 - • hits cycle 4
"'0
(1)

-

~ 400

.!!a E.-G 200. . relaad

::I:
W U

« -co

0

20

- 40

I

,

,

......

.d-II"!~-:..r:,-'"

I

,

I

2000

/
I

'" ~ .".

I

80

100 120 140

1000_'" r-'_"I' ~60

Shell under Compression
h'tI S ._.
I

4000 I - hits cycle 1 (x 12) I""-- hils cycle 2 (x 2.5)'
3000 I
hits cycle 3 ""Ihits cycle 2

---~­

hits
hits cycle 11 (x 8)hits cycle 13 (x 4)hits cycle 15

200J- ....-r--"50............. r-.

500

I

.....

,

600

""'4 reload

600

Time [5]Tube under Torsioniii 150500aTime [5]

r

,

50

100

150

200

250

300

Time (s)Fig. 6 AE Behavior during stairstep loading separated by cyclic components. Left: AE from individual reloading-loading
cycles. Right: Hold period behavior. Top: Test coupon (tensile test). Cycles S, 7 and 9 of 10. Failure by delamination on
10th hold cycle. Previous load reached at 60 s. Center: Structural element (square profile tube in torsion). Cycles II, 13 andIS of 20. Delamination visible from 15th Cycle. Previous load reached at 300 s. Bottom: Structural test (compression). 3 offirst 4 cycles (12 tota!). First ply failure by 7th cycle. Cracks noticed on 7th cycle. Failure on 12th load cycle.
The shape of the AE curves during hold changes
through the test. As the load per cycle grows, the time ittakes for emission to die out increases. In most of thetensile specimens tested under stair step loading, failure
occurred in a hold period offairly constant activity. Shonly
before failure the rate of AE accelerates. The early emis-

sions suggest a decaying curve that appears to be relatively
similar on all loading cycles.
One final question about the exponential shape during
static and stair-step loading arises. How do the exponential
rates compare between static and stair-step tests? Such a74

Time [s] in Static Test
125

0

600

250

375

Stairstep cycle
Static Tensile Data..... 500w.!
ce:c
"C ...... 400

::sn

6000

CDc

CD..!!

-u 300
.!!>.
::SO

Ec
::So
U
c

~-

~'1>

8000

4000

mg
=3

~m

miD
"a.

-2:'1>

200

...

2000

reloadAE'

100
0

0
20

40

60

80

100

120

140

ur m
::s

~

a(5"

Time [s] in Cycle
Fig. 7 Comparison of AE activity from stairstep and static tension. Data from GF/epoxy tests. The 7th of 10 load cycles istaken from the stair-step cycle is used. The entire tensile test (Fig. 2, upper left) is used for comparison.
superposition is shown in Fig. 7. There are a few problems
with this simple superposition of curves. Some tensile
specimens showed the local bursts just as the tubes under
torsion and the shell under compression, so a specimen thatshowed no local bursts was used. Another problem is normalizing the different scales. The comparison is encouraging in that the exponential growth behavior appears reproducible even when changing from strictly static to stair-steploading.

delamination inside the specimen is the dominant contribution to AE in GF-epoxy (material C).

The exponential increase of the cumulative and of the
AE rate curves shows that damage accumulation is continuously increasing during the test. This seems to indicatethat significant permanent damage could be induced in thespecimens even if only stressed at low load levels.

In the structural element test (tube under torsion) andthe structure test (structure under compression) presented,
the behavior is similar to tensile specimens under stair-stepload. The AE behavior of the structure, however, isselectively monitored due to specific sensor positions. The
growth rate curves are similar in shape in subsequent cycles
but there are local bursts that resolve against the generalincrease of the emission rate. The local bursts may bedamage initiation, or simply the failure of the weakest component within the specimen. When the structural elements(tubes) are subject to increases in load, they are more
susceptible to uneven stress distributions. The structure(GFRP-foam sandwich) has additional bond-lines, some ofwhich failed during the test. It would appear that thestructure is much more susceptible to local damage at an
earlier stage than the static tensile specimens.

The fact that one exponential factor describes the AE
rate and cumulative behavior of a particular GFRP material
in a large temperature range at constant load rate (strainrate) points to one dominant damage mechanism. Deviations from the exponential behavior may then be due toadditional AE generating mechanisms. Such mechanisms
could be the appearance of a different or of additional
damage mechanisms or additional noise sources (e.g.,
rubbing of fracture surfaces at lower temperatures). Exponential AE-rates interpreted in terms of damage accumulation are consistent with damage growth that is proportional to the amount of damage already present in thespecimen. The relation between AE rate behavior, damage
accumulation, and microscopic mechanisms clearly needs
further investigation. At this point it can be speculated that

The general emission behavior under stair-step is quite
comparable to a static test, especially in the growth rate.
The rates of emission are much smaller in the stair-steploading condition because much of the emission that occurs
in static loading is distributed between load and holdperiods and the emissions upon reloading and subsequent
new loading are reduced significantly after hold periods.
The local bursts may well occur in the static tests but are
just less resolvable against the constantly increasing rates of
AB. In some tests, where relatively constant rates ofemissions persisted until failure, even more of these local
bursts could be seen against the background of constant AE
rate. It appears that a large percentage of activity comesfrom progressive weakening of the material as the emission
is produced readily in hold periods and builds from

4. Discussion

4. / AE-Rate Behavior

75

practically the beginning of the curve upon each reload
cycle. This is emphasized in the shape similarity (fromsuperposition of cycles) although higher loads generate alarger number of emissions. The lower failure load is anindication that the material has weakened at lower load
levels in the stair-step cycles compared to static tensileloading.
4.2 Modeling Behavior

The exponential increase of cumulative and rate AE
signal parameters (counts, energy. hits) with time or load(tensile test at constant cross-head rate) is remarkable, inparticular since it yields the same exponential factor a for
all three AE parameters. The previous tests on the GFpolyester already showed some limitations of the procedure(Brunner et aI., 1994). At room-temperature a linear strain
rate dependence has been observed for the exponential
factor of material C, consistent with an analogous
dependence on the rate of damage accumulation. The threematerials tested so far yield different exponential factors(for A, 0.010 sec· I ; B, 0.020 sec· l ; C, 0.014 sec· I ) whentested at I mm/min. The value seems to depend on bothmatrix material and arrangement of fiber reinforcement. In
the temperature range where exponential behavior with aconstant exponential factor has been observed, the rate ofdamage accumulation and therefore quite likely the damage
mechanisms are independent of temperature.
In order to show and confirm exponential AE-rate
behavior. the superposition of rate and cumulative curves
has advantages over other procedures, e.g., semi-log plots
and least square fits. Both semi-log plots and superposition
can be accomplished easily, usually with the existing
software of commercial instruments. The least square fit
requires the value of a and additional software. The semilog plot. however, does not yield a straight line but a curvethat is asymptotic to a linear relation because the AE-rate
can not be truly exponential. An exponential has a finite
value at t 0 whereas there is no AE until after the start of
the test. A simple correction is to use an offset, such as=alAEcumulative = k(e- 1)

and this, in fact, appears to be the behavior of the AE-rate
curves for the tensile specimens.
The AE-rate for material C is exponential, except
below about 30° C. The results presented for materials A
and B show that the AE-rate and cumulative curves are
exponential and transitions to a different behavior occur
above and below certain material-dependent temperatures.
An "AE knee" (as proposed by Mitchell, 1989), Le.• achange in the slope of the AE signal rate and of the
cumulative AE curve, therefore, occurs only in a limited
temperature range and maybe not for all GFRP composites.
A definition of the knee-point for the purely exponential

range (e.g.• material C between -30 De and +140°C) or in
the purely linear range (e.g., material A at -20°C) would bearbitrary and not based on detectable changes in the damage
mechanisms or in the rate of damage accumulation.
S. Conclusion
Epoxy specimens with 0°/900 glass-fiber rovings as
reinforcement yielded an exponential AE-rate (proportional
to eat as measured by three AE signal parameters) whentested up to failure in static tensile tests. The exponential
factor a remained constant in the range between -30° and+ 140°C and is characteristic of the damage accumulation ofa material under load. An exception from the exponential
behavior of the AE rate has been observed for temperatures
below -30°C. The results suggest that the exponential
factor is different for each type of matrix material and layup.
There are significant similarities in the AE activity
behavior in the tensile specimen, structural element andstructural tests presented under stair-step loading programs.
The similarities in behavior show up mainly in the shape of
the AE occurring on subsequent cycles in both reloadloading cycles and hold periods. The best way to model the
reproducible part of the behavior is to introduce parameterswhich separate shape from scale; that is, the use of aminimum of two parameters. The shape is the one aspectof AE-rate behavior studied here that was consistent
between static tensile testing. stair-step material testing andstructural element testing. These similarities are importantin understanding AE-material behavior and how it differsfrom diagnostic (field test) analysis of AE.
Exponential behavior of the AE-rate is consistent with
one dominant damage mechanism (e.g., delamination) in
the specimens. A hypothesis that eJtplains why deviationsin the exponential AE behavior arise is that additional AE
generating mechanisms become significant. This yields a
new interpretation of the knee in the AE-rate andcumulative curves. If one damage mechanism is dominant,then no knee is observed in the AE behavior. If more thanone AE generating mechanisms (two or more damage
mechanisms or AE noise sources) contribute to the AE
behavior. the transition from one to more than one
mechanisms becomes apparent as a knee in the AE-rate andcumulative curves.
References

J. Awerbuch (1988), "On the Identification of Failure
Mechanisms in Composite Laminates trough Acoustic
Emission." Acoustic Emission, ed. I. EisenbUitter. DGMInformationsgesellschaft, Oberuesel, Germany, pp. 47-58.
A.I. Brunner. R. Nordstrom and P. FlUeler (1994),"Schallemission bei kombinierter thermisch-mechanischer

Belastung von glasfaser-verstiirkten Zugproben, " Proceedings 10. Kolloquium Schallemission (in Gennan), Deutsche
Gesellschaft fUr Zerstorungsfreie Prlifung, vol. 42, pp. 181-

Crack Damage Evolution in Rocks and Subsurface Rock
Structures Modeled from Acoustic Emission Data", J.
Acoustic Emission. 13(1-2), S21-S28.

190.

K. Takashima, H. Tonda and P. Bowen (1995), "Acoustic
Emission and Damage Evolution in an SiC Fiber Reinforced Ti Alloy Composite".J. Acoustic Emission, 13(1-2),
S8-513.

AJ. Brunner, R. Nordstrom and P. F1Ueler (1995), "TwoParameter Description of the AE-Rate Behavior of GlassFiber Reinforced Epoxy and Polyester under Static Tensile
Loading," Proc. Fifth International Symposium on Acoustic
Emissionfrom Composites, AECM-5, July 10-14, Sundsvall, Sweden, ASNT, Columbus, pp. 101-110.
Committee on Acoustic Emission from Reinforced Plastics(CARP) of the Composites Institute, the Society of the
Plastics Industry, Inc. (1987), "Recommended Practice for
Acoustic Emission Testing of Fiberglass Reinforced Plastic
Resin (FRP) TanksNessels," August 1987, 14 pages.
TJ. Fowler (1986), "Experience with Acoustic Emission
Monitoring of Chemical Process Industry Vessels,"
Progress in Acoustic Emission III, Japanese Society of
NOI, Tokyo, pp. 150-162.
TJ. Fowler, J.A. Blessing and PJ. Conlisk (1989a), "NewDirections in Testing," Proc. Third International Symposium from Acoustic Emission from Composites, AECM-3,
Paris, France, July 17-21, ASNT, Columbus, pp. 16-27.
TJ. Fowler, J.A. Blessing, PJ. Conlisk and T.L. Swanson(1989b), "The MONPAC System," 1. Acoustic Emission,
8(3),1-10.
TJ. Fowler, J.A. Blessing and P.l. Conlisk (1992),"Intensity Analysis," Proc. Fourth International Symposium on Acoustic Emission from Composites, AECM-4,
July 27-31, Seattle, WA, ASNT, Columbus, pp.237-246.
M.A. Hamstad (1992), "An Examination of Acoustic
Emission Evaluation Criteria for Aerospace Type Fiberl
Polymer Composites," Proc. Fourth International Symposium on Acoustic Emission from Composites, AECM-4,
July 27-31, Seattle, WA, ASNT, Columbus, PP.436-449.
J.R. Mitchell (J 989), "Standard Test to Quantify the Kneein the AE vs Load Curve as a Material Parameter for
Composites," Proc. Third International Symposi/lm on
Acoustic Emission from Composites, AECM-3, Paris,
ASNT, Columbus, pp. 207-219.
R. Nordstrom and AJ. Brunner (1995), "Discrimination of
AE Phenomena in Composite Testing," Proc. Fifth
International Symposium on Acoustic Emission from
Composites, AECM-S. July 10-14, Sundsvall. Sweden,
ASNT, Columbus, pp. 91-100.
P. Samrnonds, P. Meredith, 1. Gomez and I. Main (1995),"The Interaction between Pore Fluid Pressure Changes and77

Future Meetings on AE
The 39th Meeting of the Acoustic Emission Working Group, March 26-28,
1996, Dana Point Hilton Inn (AE Primer on March 25)
For more information, call or e-mail to
Hal Dunegan, Meeting Chainnan
Dunegan Engineering Corporation
Hotel reservation (714)-661-1100
Phone (714)-661-8105; Fax (714)-661-3723
e-mail: hal@deci.com; http://www.calypso.comldecil

The 22nd European Conference on Acoustic Emission Testing,.
incorporating EWGAE, May 29-31, 1996, Aberdeen, UK
For more information, write to
Meg Thain, Conference Organizer
The Robert Gordon University
Kepplestone, Queens Road, Aberdeen AB9 2PG UK
Phone (44)-1224-263322; FAX (44)-1224-263323
e-mail: m.thain@rgu.ac.uk

The 6th Conference on AEIMS in Geologic Structures and Materials, June
11-13, 1996 at Pennsylvania State University
For more infonnation, write toProf. H.R. Hardy, Jr.
110 Hosler Bldg, The Pennsylvania State University
University Park, PA 16802
Phone 814-863-1620; FAX 814-865-3248

The 13th International AE Symposium (IAES 13), November 27-30, 1996,
Nara, JapanFor more information, write toProf. Y. Higo, Program Chairman
Tokyo Institute of Technology, 4259 Nagatsuda, Midori-ku
Yokohama 227, Japan
Phone (81 )-45-922-1111, x2044; FAX (81 )-45-921-0898
e-mail: yhigo@pi.titech.ac.jp

The 14th World Conference on Non-Destructive Testing, December 8-13,
1996, New Delhi, India
For more information, write to
Dr. BaJdev Raj, President, International Committee on NOT
Director, Metallurgy and Materials GroupIndira Gandhi Centre for Atomic ResearchKalpakkam 603 102, Tamil Nadu. India
Phone (91)-4117-301/356; FAX (91)-4117-360
e-mail: dmg@igar.iitm.ernet.in
78

The Deterioration of Foamglas® under Compression
Studied with the Acoustic Emission Technique
M. Wevers, D. Tsamtsakis, P. De Meester, E. Una and H. Strauven
Abstract

possibilities of the acoustic emission (AE) technique. aresome of the reasons. which explain the increasing interestfor the use of AE for the evaluation of the integrity of astructure.

The mechanical behavio r of foamed glasses duringsimple compression and cyclic trapezoidal compression
tests has been studied using the acoustic emission (AE)technique for damage monitoring. Different types of
foamed glass materia) were tested and AE parametelS suchas the tOlal number of AE events. the relative energy of the
AE events. the force at the time of continuous increase of
AE activity and the slope of the events versus time curve
were derived for each type of material. We attempt to correlate the AE results with the mechanical behavior of thematerial. Felicity ratios are also calculated. It is shown thatan estimation of the structural integrity of the material atdifferent load levels is possible.

The main advantages of AE as a non-destructive technique arc:
• High sensitivity to detect growing defects.
• Strictly passive method. The material itself generates
the signals to analyze.
• Indicates the existence of a defect. eventually gives
its location and sometimes can be used to estimate the severity of damage (i.e. Felicity ratio measurements).
• It can be applied for real-time monitoring during the
manufacturing stage as well as the in-service control.
However. the material must be under applied stress conditions in order to allow energy to be released from thegrowing damage or defects. Moreovcr. to perform reliablemeasurements. a good contact between the material and thesensors as well as appropriate noise elimination have to be
assured.

1. Introduction
New products used in modern industrial applications
take advantage of the improved methods of structural design technology and it is now possible to achieve the desired physical and mechanical properties by applying
highly specialized manufacturing methods; fabrication of
three dimensional cellular solids for instance. Apart fromtheir good insulating properties. foamed materials developed for use in thermal insulation applications (such as
underground piping. roof and floor constructions. tankbases. etc.) must fulfill certain strength requirements. In thecase of critical load bearing applications. they must withstand compressive loads without considerable reduction of
their structural integrity. Therefore. an extensive quality
assessment. including the use of non-destructive inspection
tcchniques. has to be carried out before the product is introduced to the market. The improvement of instrumentation and the development of new materials (like composites). for which the usual non-destructive evaluation methods are not so suitable and also. a more realistic idea of the

In this research. the behavior of Foamglas® undersimple compression and cyclic trapezoidal compression
loading is stUdied. using the AE technique to monitor thedamage development. Felicity ratios for the different stagesof the compression loading have been calculated and used
for analysis.
2. Experimental Details

2./ Materials
The material used in this investigation is Foamglas®. aproduct of Pittsburgh Coming. This is a light-weight. rigid
insulating material composed of millions of completely
scaled glass cells (F~. I). A view of the surface morphology of the Foamglas is shown in Fig. 2.

Received 28 September 1995. The first four authors are affiliatedwilh Department of Metallurgy and Materials Engineering. K.U.
Lcuven. Leuven. Belgium (martine.wevers@mtm.kuleuven.ac.be)and H. Strauven is with Pittsburgh Corning Europe NV. Tessenderlo. Belgium. This is based on a paper that was presented at
the Fifth International Symposium on Acoustic Emission from
Composites. AECM-5. Sundsvall. Sweden and was included in
the proceedings volume published by The American Society for
Nondestructive Testing. Columbus. OH.
JoumBl of Acoustic Emission
Volume 13. Number 3/4

Gibson and Ashby (1988) proposed a cubic cell model
for closed cell foams. Each cell element (Fig. 3) is composed by the cell edges and the cell faces. This cell model
will be used as a reference for the fracture behavior of
Foamglas®. Each cell is an insulating space. Thanks 10 its
closed-cell structure and to its eight exceptional properties(water vapor proof. waterproof. dimensionally stable. noncombustible. high compressive strength. vermin proof. resistant to acids and easy to work). it has the necessary bene79

07JO-(1Os0t951S5.0011 3079-086
Copyright@I995 Acoustic Emission Groupfits which make it ideal for piping and equipment above
ground. indoors and outdoors at operating temperaturesfrom -26()OC to +430°C (Pittsburgh Corning Europe,"Cellular glass in industry", Foamglas" information brochure).
There are five types of Foamglas" which have beenstudied in our research program. The density and thestrength in compression as given by Pittsburgh Coming
Europe arc listed in Table I. All specimens used in thisstudy were cubic blocks wilh the dimensions of 100 x 100
x 100 0101 3 .

2.2 £'(perill/l'lIlc1l Selup
The experimental setup for the compression tests withAE monitoring of the Foamglas" specimens is shown in
Fig. 4. Compressive tests have been carried out on an I nstron 1196 testing machine with a maximum load capacityof 250 kN. The speed of the crosshead during the tests was
adjusted to 0.1 nun/min. The AET 5500B acoustic emission
system of the Acoustic Emission Technology Co. was used
to monitor the AE signals produced by the Fmllnglas ... The
test settings of the AE system arc shown in Table 2.

A resonant AE transducer. model AC 375L of AET Co.
with a nat frequency response in the low kHz range wasmounted on the side of each specimen (Fig. 4). The gain of
the preamplifier was fixed at 40 dB and the signals werepassed through a bundpass (250-500 kHz) filter. For the
coupling of the transducers on the specimen, the SC-6 silicon based couplant was used. The following graphs havebeen set for the AE recording during all the tests:• number of events versus time.
• total number of events versus time.
• distri bUlion of events versus analog pammeler(applied force).
• distribution of events versus peak amplitude.
• distribulion of events versus energy.
Two types of compression tests have been conducted
10 siudy the mechanical behavior of the Foamglus .. :• simple compression,• cyclic trapczoidul compres sion.
All tests were performed in a displacement control mode. A
schematic reprcsentation of the imposed loading is shownin Fig. 5.

Table I Density and strength in compression, for the di fl"crelll types of Foamglas" .
Dma given by Pittsburgh Corning Europe.
Type of Foamgla"
F
1'2
1'4

T4P
T4W

.

Density Ikglmjl
175
127
126
116
110

Fig. I Scanning eleclron microscope picture of the closed
cell structure of a foamed glass material (Pittsburgh Cor ning Europe).

Strength incompression [MPa]
1.70
1.00
0.80
0.80
0.65

Fig. 2 Oplical microscope picture of lhe surface morphology of Foumglas ,. .

Table 2 Acoustic emission parameters and settings.
Clock period of Event Duration
Clock period of Rise Time Module

250ns
125 nsThreshold
Preamplification

0.2 Volts
40 dB

Range settings
Ring Down Counts
Event Duration
Rise Time
Peak Amplitude
Ener2V

1-40951-65520 IlS
1-65520 IlS
0-117 dB
0-165 energy units

Fig. 4 EXlIDrimental set up for the compression tests ofFoamglas specimens.

Fig. 3 Cubic cell model for closed cell foams.

Time

Time

a

b.

Fig. 5 a. Simple compression loading, b. Cyclic trapezoidal compression loading.

81

3. Damage Mechanisms
According to the model of Gibson and Ashby (1988),
three main mechanisms of deformation occur during thecompressive loading:• bending of the cell edges at the initial stages of loading under linear elastic deformation (Fig. 6a),• stretching of the faces (membrane stretching) as
shown in Fig. 6b,• fracture of the cell edges and formation of a cracked
area propagating through the material (Fig. 6c).
From the above mentioned failure mechanisms, mainly thelast one contributes to the release of energy and therefore
generates acoustic emission.
4. Results and Discussion

4.1 Simple Compression
Five ~cimens of each of the five different types of
Foamglas were tested in compression until fracture. A
typical load-displacement plot is shown in Fig. 7. One of
the most important parameters for the damage assessmentof the material is the time at which the material begins toemit AE signals continuously. This time value can be provided by the events versus time plot (Fig. 8), which record
the AE activity generated by the material until final ruptureof the specimen. From the load versus time plot, the load
value corresponding to that particular moment of contin uous increase of AE can be defined. The curve of the total
events versus time plot can be used for the definition of theslope of the line drawn tangential to the final, almost linear,part of the curve. This is shown schematica1ly in Fig. 9.
The higher the slope, the larger the accumulation of damage in the material. The distribution of events by energy[Energy = Peak Amplitude + ]0 log (Event Duration) )could be used to discriminate between the different damage
mechanisms during the loading of the material and an average value of the energy content of the AE signals can bederived. The results, i.e., mean values of five tests andstandard deviations, for each type of Foamglas<E are presented in Table 3. These results are also depicted as histograms in Fig. 10.

aunstrelehedstretchedb.

FF
broken celledges

The deviation observed between the values of max imum force obtained by the experimental results and thosegiven by \he company is explained by the fact that the material is not isotropic regarding its mechanical properties asa result of the manufacturing process. A tolerance of ] 5%
was acceptable by the manufacturer for the compression
strength.

c.

Types F, T4 and T4P of Foamg]as ® exhibit a stablebehavior on the values of the different AE parameters described above (sma1l standard deviations). Types T2 andT4W, however, exhibit a larger scatter on the features

Fig. 6 Three main deformation mechanisms of the foam
cell: a. cell edge bending; b. stretching of the faces; c. celledge fracture.
82

15.0 F'Sh: "3.D.. re.te" r. 3. M.t.: Foa...,' ... lOla... 503,. Black C."bonl

13.5
12.0
10.5
9.0

-.

Z

7.5

~

........
0

IS.O

~

"0

t=..

".5
3.0
1.5

0.0
0.0

O.z

0.4

0.1

0.8

1.0

1.2

S."

1.8

z.O

S.'

Head Displacement (mm)Fig. 7 Typical load-displacement curve for a compression test of Foamglas ®

II

I

t

Time

Time

Fig. 8 Events versus time plot for the definition of the timeof continuous increase of AE activity.

Fig. 9 Total events versus time plot for the definition of theslope.

extracted from the AE plots, which are related to the mechanical behavior of the material (tolerance of 15% is often
exceeded). It seems that the first generation of Foamglas ~(types F and T2) exhibit better mechanical properties. Thisis also confirmed by the higher values of the load at which
the AE activity begins to increase continuously. It was also
observed that the types T2 and F of Foamglas ~ show atendency to produce more AE events in comparison to theT4 series.

4.2 Cyclic Trapezoidal Compression

No particularly good correlation between the fractureload and the slope or the mean value of the energy distri·bution was found. However, as the fracture approaches,more and more high energy signals are recorded and thiscan be considered as an indication for imminent failure.

With the cyclic trapezoidal compression loading, theFelicity effect is studied and Felicity ratio values are deduced for different levels of damage. A trapezoidal loading
sequence is applied with a load hold for a time period of
120 s plus the time needed for the total cease of acoustic
emission. Then, the load is set to zero and a new loading
cycle begins. A schematic representation of the ideal loading sequence is given in Fig. 5b. A maximum of five loadholds was decided to be applied. The real loading cond itions during this cyclic trapezoidal compression test are
shown in Figure 11 a which is a load-time plot as recordedby the Instron testing machine. A load drop due to relaxation mechanisms is observed during the constant displace

Table 3 Results from the tests in simple compression on Foamglas®. Standard deviations are indicated between brackets.
Material Type
Fracture load(kN]
(as given by the
comDanv)
Experimental
fracture load

F17
(2.55)

TI
10
(1.5)

T4
8
(1.2)

T4P
8
(1.2)

T4W
6.5
(0.975)14.43(2.22)

13.24(5.11)

6.64(0.70)

8.17(1.08)

9.48
(1.9)

4.2
(0.86)

3.34( 1.03)1.63(0.70)

1.50(0.49)

1.73(0.78)

19166(4736)
2.34(0.22)

22917(9584)
1.81(0.37)

9646(2383)
1.90(0.31)

18583(1520)
2.41(0.37)

17479(5287)
1.88(0.79)

83.4(0.72)

79.2(2.32)

83.2
(1.3)

85.8
(0.9)

79.4
(4.4)

(kNJ

Load value at thetime of increaseof AE rteNl
Total number ofAEevents
Slope of the total
events vs. time
plot
Mean value ofenergy distribution

Table 4 Felicity ratio results from the cyclic trapezoidal compression tests for the different types of Foamglas~.

Load rkNl
J

1.5
2
2.5
3
4
4.5
5
6
7.5
8
10
12.5

F

TI

-

·

.

1.06

1.352

-

-

T4

T4P

-

-

.

-

-

-

1.13

0.76
0.6

0.43
0.40

0.95

-

·

0.93

-

0.576
0.38

-

-

0.66

0.75
0.76

·

-

0.15

-

0.9

-

0.65

-

-

.

0.8

0.8

T4W
1.26

-

·

0.68
0.5

0.40

-

·
·
-

more recent generation (T4, T4P) with the exception of thetype T4W. However, the Felicity ratios for types T4Wand
T4 show a tendency to stabilize as the load increases.

ment period. A time window corresponding to each cycle isdefined on the AE graph of events versus time (Fig. lib;
test duration = 38.5 min) and the moment of increase of AE
events (in a way similar to that of simple compression tests)
is determined. Then, from the load-time plot provided bylnstron. the load value corresponding to that moment isdefined. Therefore, the calculation of Felicity ratios (FR)for every load hold is carried out using FR = F 2/ F I in
which F I is the last load hold value and F 2 is the load value
at which AE activity resumes upon loading.

Although it is not possible to make a clear discrimination between the different types of Foamglas®. based on
the Felicity ratio, it is still possible to estimate the amountof damage developed in the specimen. A Felicity ratio of
the order of 0.9 for the Foamglas®, indicates a material
which can still remain in service, while a ratio of 0.5 is anindication for a seriously damaged material and a removalfrom service is recommended. However, more research
work has to be carried out on this topic in order to verify
the accuracy of these values for the Felicity ratio.

The results for the different types of Foamglas@ aresummarized in Table 4. The graphical representation ofthese results (Fig. 12), reveals that the first generation of
Foamglas@ (F, TI), exhibits lower Felicity ratios than the84

18..-. 16~ 14.......
u 12
g 10
~

5

e 8

a

.~

6
4

~ 2

o

F

12

T4

T4P

T4W

F

12

Material type

T4

T4P

T4W

Material type

1f2.
~
~

s::: 1.5~
8.Q 0.5....... 1.0
rJ)

o

F

12

T4

0.0

T4P

1'2

F

T4

Material type

Material typeFig. 10 Results of the compression tests for the different
types of Foamglas®.
F

1'2

T4

Material type..... r, 'II': c•....,.o.. ..,.. f: I.

20

...

e.•

z,..

-

~

1.1

~

s••

-

-

-4l-.1.-41-H

to.9Time (sec)
a.

-

b.

EVEKT~

us Tint rON StKSOR I

Fig. II a. Real cyclic trapezoidal loading in compression; b. Events vs. time plot for a cyclic trapezoidal loading .
Il5

1.4
1.2

tiio

--+-F
-x-12

~

-.-T4

=

~T4P

.. 0.8:g 0.6
~ 0.4

_T4W

0.2
0+----+----+----+----+----I-----4f---~

o

2

4

6

8

10

12

14

Load (kN)
Fig. 12 Felicity ratio calculations for the different types of Foamglas®.

5. Conclusions
The mechanical behavior of Foamglas~ under simple
compression and cyclic trapezoidal compression has beenstudied using the AE activity of the material under compression for analysis. These tests in compression indicatethat the AE activity of the Foamglas® depends on the typeof glass and the foamed structure. Different types of
foamed glasses can clearly be identified by the compressive
force at which the AE activity increases and the total number of AE signals detected at failure. The relative energy ofthe detected signals close to compressive failure of the
Foamglas ® is high, compared to the average AE signal
energy, detected during the compression test and might beused as failure criterion. The cyclic trapezoidal compression tests provide more information about the damage development in the foamed glasses and the Felicity ratio
seems to be a measure for this.

References
L. Gibson and M. Ashby (1988), "Cellular Solids. Structures & properties", Pergamon Press, London.

86

Localization of Acoustic Emission in the Fracture of Fiber
Composites
Vladimir Krivobodrov
Abstract

The purpose of the present work is to investigate themechanisms and to determine which characteristics ofstressed samples can affect the AE localization. For thequantitative study of AE localization, the measure of localization needs to be defined. Such a measure should be available for experimental evaluation and, also, for calculationon the basis of one or another model. In the present work
AE signals are considered as fracture initiated events, therefore comparing theoretical models with experimental data
we consider AE signals and microfracture events as equiva-lent.

Distribution of acoustic emission (AE) signals withincomposite materials during deformation is studied. The present research has shown that the AE localization occurs due
to tWO main reasons of a different physical nattire: initial
distribution of defects in the material and nonlinear dependence of microfracture probability upon applied stress. The
dimensionless parameter characterizing AE localization:
Parameter of Localization (PL), has been introduced. It isshown that the distribution of internal stress concentrations
can be evaluated by the initial part of the PL vs. appliedstress curve. This technique can be employed for nondestructive testing. Comparing experimental data with theoretical models has shown that different fracture mechanisms
demonstrate a different dependence of PL on applied stress.

2. Experiment
Divide virtually all volume of a sample, V, into subvolumes, vm' m = I...M. The microvolume size should bewithin the range d 3«vm«V, where d is a fiber diameter.
Available AE registration techniques allow to register asignal location within the accuracy of down to I mm. Thismeans that we can unambiguously attribute each registeredsignal to a subvolume with dimensions of ] mm or more.
Since a typical AE signal is connected with a fiber break,and the fiber diameter is about ] 0 Jlm a subvolume withdimensions in the millimeter range contains enough elementary units of composite structure to provide a statistically significant number of AE signals.

1. Introduction
Experiments have shown that macrofracture of fiber
composites during deformation is preceded by the accumulation of microfractures - single fiber breaks and groups ofbroken fibers, matrix microcracks, debonding, microcracks
on a fiber/matrix interface, etc. (Rosen, 1964; Zweben,]968). These microfractures are associated with the generation of acoustic emission (AE) signals. Location of AE
source coordinates by multichannel AE registration techniques has shown that the spatial distribution of signals
within a composite subjected to stressing is inhomogeneous. When the applied stress is increased in a material, there
can be distinguished a region where AE signals are predominantly generated (Krivobodrov and Gubanova, ]989;
Gavrilin and Krivobodrov, ]989). Formation of such a
region means that there is a localization of AE in a composite during deformation. The localization takes place evenin the case of a uniform stress distribution within tested
samples.

For each value of applied stress s. we can measure thenumber of AE signals in each subvolume. As a result weobtain the array Nm(s.), where m numerates subvolumes andN m is the number of AE signals registered in moth subvolume, andM

N(s.) =

m=1

is the total number of signals measured in a sample atstressing from 0 to s•.
The array Nm(s.) is the basic type of statistical datacharacterizing the space distribution of AE signals within asample, which can be obtained from experiments. The purpose of the following rearrangements is to present the statistical information in the form most convenient for evaluation. From the viewpoint of the statistical theory, the conventional procedure is to obtain from the experimental arraythe probability density, v(n), which characterizes the relative volume of a sample containing the number of signals

Received 26 November 1995. The author is affiliated with Research Centre "Composite", P.O. Box 28, St. Petersburg,
194017, Russia. (krv@zaitsev.ioffe.rssi.ru) This is based on apaper that was presented at the Fifth International Symposiumon Acoustic Emission from Composites. AECM-5, Sundsvall.
Sweden and was included in the proceedings volume publishedby The American Society. for Nondestructive Testing. Columbus.OH.
Journal of Acoustic Emission
Volume 13. Number 3/4

L Nm(s.)fJ1

0730-00501951$5.00/13087-096
Copyright@1995 Acoustic Emission Group

within the range [no n+dnl, and then evaluate the averagevalue of n and the dispersion.

constant strain rate of 0.0001 min". The stress-strain curveof the samples remained linear up to failure.

In contrast to conventional statistics in fracture studies,
we are interested in the extremities rather than average values. This means focusing on the subvolumes containing
the maximal number of AE signals. Unfonunately, theaverage values are not sensitive enough to the distribution
behavior in the area of large deviations from the averagevalue. That is why, for the fracture studies, we decided to
introduce another parameter characterizing the relative volume of a sample involved into the most intensive microcracking process. (In tenns of acoustic emission. thisparameter evaluates the relative number of subvolumes having the maximal amount of AE events.) For this purpose adimensionless parameter. which we call "Parameter of L0calization", PL. was introduced. The value of PL is determined as the ratio of the size of two volumes. One of themis the total volume of a sample in which AE is registered.
The other volume the a minimal volume of a body, inwhich 50% of AE signals have been registered. The choiceof 50% is arbitrary and we choose 50% because in this casethe relative experimental error of measuring PL is minimal.

The AE signals generated during deformation of thesamples were recorded in the one.dimensional location technique, i.e., only the coordinate of the AE signal source
along the sample length was registered. In Fig. IA. theintensity of AE signals registered In cross sections of asample of CFRP as a function of strain is presented. 1l1e
coordinate was counted from the time difference between thesignal reaching the two sensors attached to the opposite
ends of a specimen (see Fig. IB). The error of determinationof the coordinates was under 2.0 mm. The sensors were of aresonance type with the resonance frequency of 400 kHz.
The selection of registered signals in the amplifying pan ofthe electronic system made it possible to store in the computer memory only the signals of a large amplitude corresponding to the single fiber breaks. and breaks of fibergroups.
Whenever the coordinates of AE signals were determined. the data was processed funher in accordance with thegeneral procedure described above: the sample was vinuallydivided into 50 sections along its length and the number ofsignals registered in each section was counted as a functionof applied stress. Then, for a given value of s" the arrayNm(se) was formed. where m stands for the section number(m = I to 50) and N m is the number of AE signals registered in the m-th section of a specimen at loading from zerostress to Se' The obtained array. N m• was rearranged in doscending order into array Nt, the value of K was determined
and the value of PL for chosen value of applied stress Se
was calculated, after which the procedure was repeated forthe next value of Set etc.

One can see that Parameter of Localization is a function of applied stress. PL PL(se)' From the definition it
follows that PL(se) varies within the range [0. 0.5]. Valuesof PL(se) close to zero correspond to a maximally localized
process, whereas, at PL(s,,) = 0.5. AE signals are uniformly
distributed throughout the bulk of the material.

=

The experimental procedure to determine the PL values
is as follows. For a given value of applied stress Se we obtain an experimental array Nm(se)' Then, by means of computer facilities this array is rearranged in descending orderfrom the maximum to the minimum value and as the resultof this procedure the array N" is formed. Then. in the array
Nt we chose the first K terms to the effect thatK

The obtained function PLeSe) is presented in Fig. 2(curve a), as well as the cumulative AE event counts registered upon stressing of the sample (curve b). It demonstrates
that the PLese) plot can be divided into three segments. At
the initial stage of the loading (segment I in Fig. 2), there
are no signals of AE; therefore, experimental function
PL(se) can not be defined in this segment. In segment IT thevalue of PL changes from zero to PL = 0.16, after which it
remains unchanged up to fracture (segmentin the Fig.
2). The error of determining PL in experiments amounted to
0.01. Comparing curves a and b in Fig. 2 one can see thatthe process of intense AE signal generation occurs at a practically constant localization.

K+I

I,N k S NI2 and I,N k > NI2.
k=1

k=1

The value of PL, then. is calculated as the ratio of asummed volume of the first K subvolumes corresponding
to the rearranged array Nt to the total volume of a sample.
In case all chosen microvolumes are of an equal size we cansimply write PL(s,,) KIM.

m=

In our experiments, the dependence PL(se) was measured for carbon fiber reinfoR:ed plastics (CFRP) consistingof high modulus carbon fibers and low modulus ductile
matrix. The samples were fabricated from carbon fibers
ELUR-P-o.1 and epoxy resin ED-20. The material was pr0duced by extrusion technology. The volume fraction of fibers was V r = 60% and the average diameter of the fibers
was 10 J.lm. The samples were made in the "dog bone"
shape with the working pan 10 cm long. and cross section
5.0 x 1.0 mm. The tension was applied along the fibers at a

The form of obtained PL curve turned out to be unexpected. Based on theories of composite fracture (Rosen.
1964; Zweben. 1968). the expectation was that in the initial stage of deformation the localization of microfractures
will be minimal (PL is at maximum). and will increase
with deformation due to nonlinear stress.dependence of microfracture probability.
8B

AE intensity, events/sec

A
15

10

5

50
Coordinate along a sample, mm..------...

_--.
B

2
Fig. I Intensity of AE signals registered in cross sections of a CFRP sample (I) vs. strain and positions of AE sensors (2).

0.18

c:

II

III

3000

0.16
2500

0

.. 0.14co....c::laCJ....ctnN

10 0.12

Q)

CJ

>
Q)

't-

1500 W

a 0.1

«

0

..

~ 0.08

....
Q)

Q)

1000 >a~ 0.06

~

to
m
0.04

a..

::J

500

0.02
0

0.3

0.6

0.9

E

:l
()

0

Applied stress, GPa
Fig. 2 (a) Parameter of Localization vs. applied stress and (b) cumulative AE event counts registered in a CFRP sample.
S

The experimental behavior of the Parameter of localization can be explained on the basis of known composite
fracture models provided two additional assumptions are
introduced:(i) there is a region (regions) of local stress concentration within the bulk of a sample and(ii) the fibers start to break whenever some local
threshold stress, s" is reached.
The first additional assumption explains why only few
sections of a sample are involved in intensive microcracking. The supposed inhomogeneity of internal stresses canbe due to residual stresses and/or to the presence in a sample
of internal structural defects such as voids, incompletely
impregnated areas, variation of adhesion of matrix to fiberalong the fiber, etc. acting as stress concentrators. Since theflow stress ofa plastic matrix is quite low, one can hardly
expect high values of residual sttesses in the sample. Therefore. to make things easier. only the internal stress concentrations will be further considered. (The effect of residual
stresses can be accounted for in the same way.)
The second additional assumption explains segment Iof PL(se) curve as a region of applied stress. at which internal stress in all cross sections of a sample is lower than thethreshold value. In segment II of the curve due to local
stress concentration at some sample cross sections thethreshold stress is already reached while at others it is stillnot. Fracture processes can generally be considered at the
sample's cross sections as a self-similar process, but developed at different cross sections to different stages corresponding to different actual stresses acting upon them. The
ascending part of the PL curve corresponds to a gradual involvement of new sample sections into a similar process.
The segment III of the PLeSe) curve in Fig. 2 corresponds tothe material state in which, at alt the cross sections, thethreshold stress is reached and. in all sample sections, thesimilar process of microfracture accumulation takes place.
The difference between the sections is in stress acting uponthem and. therefore. in a stage of microfracture accwnulation.
In the suggested model the increase of the Parameter ofLocalization corresponds to the more and more sites within
the material being involved in the fracture. The decrease of
PL results from nonlinear dependence of probability of microfractures on the applied stress.
In accordance with the assumptions made above, thegeneration of the first AE signal in a section serves as akind of indicator demonstrating that the local stresses inthis section have reached the threshold value Sl' The beginning of segment ill of the curve signifies that at the crosssection with the minimal stress concentration, taken as
unity by definition. the internal stress has reached thethreshold level. Therefore, we can roughly determine s, as
the stress equal to the applied stress at the beginning of thesegment III of the PL(s.) curve. As soon as s, is determined
we can determine the stress concentration profile in thespecimen's cross sections by dividing stress Sc by the external stresses at which first signals in the sample sections areregistered.
For the analytical model we need the stress concentration distribution function rather than the stress concentration profile. The distribution function of internal stressconcentrations can be obtained from segment II of the PL
curve.
The peculiar feature of segment II of the PLese) curve isthat at this stage in some sample sections AE signals havealready been registered whereas in other sections stilt not. In
this case, PL values can be calculated on the basis of thesections in which AE signals have been registered. Thisvalue, PLmD' is connected with the value of PL calculated
in the case when all cross sections are accounted for regardless of the availability of registered AE signaJs by the equation
PL = PLmu ( I - Q).
(l)where Q is the share of sample cross sections in which atapplied stress Se the internal stress is lower than s,. i.e.
Ss

Q(Se) =

Jp(s)ds(2)s.
where p(s) is the probability density of internal stresses.
Taking into account that in segment n of the PLese)curve one can write for the coefficient of internal stress concentrations k = sIs. for the distribution function of coefficient of internal stress concentrations Q(k). we have fromequations (I) and (2)Q(k) = I - PUPLm...
In case the threshold stress is reached in all sections of asample we have Q = 0 and can write PL max = PL(sr)' am
also, since in segment m of the plot the PL(s,) remains
unchanged. it can be supposed that PLmax value in segment
n is the same (or the same within the accuracy of experimentaJ data) as in segment III. (This assumption
later
be confirmed by theoretical calculations).

wi"Figure 3 shows the function Q(k) obtained from theexperimental PL(s.) curve presented in Fig. 2 . It demonstrates that experimental points can be approximated by astraight line. which corresponds to the density distributionfunctionatk e (l,kmaxllI(k max -1)
p(k) ={
0
at k < I and
k>k
(3)
nw

The value kmu can be determined from the point of intersection of the curve Q(k) with the line Q(k) = I. For our experimental data we obtain k.nu 1.7. From the experimental data of distribution of AE sources within a sample themagnitude and distribution of internal stress concentrations
can be evaluated. The stress concentrations of this kind are=1.2r--------------------~

c

o

:;

oc

1 -------------------------------- ------

.2

.

c 08
0

.

;j

:s..0 0.6
CIJ

-c
~ 0.4

:;
~

;j

E 0.2

;j

t)

ol..-----....:.....----''----------------I
o
1.0
1.5
2.
Coefiicient of internal stress concentrations
Fig. 3 Distribution function of the internal stress concentrations in the cross sectionsof a CFRP sample obtained from the experimental PL(sJ curve.
apparently introduced into a composite during the fabrication process. Therefore. the multichannel AE technique canbe employed for the quality control of produced materials.
This quality control can be conducted at stresses lower thanfracture stress and, hence, the complete testing of fabricatedcomposites can be provided by the use of multichannel AE
registration technique.

According to the model a composite consists of a seriesof identical layers of elements whose axial dimensions aresome ineffective length d . Any fiber that breaks in a layer
is considered to have zero stress within that layer, but to be
fully stressed in all other layers. The initial number of unbroken fibers in the layer is NOt and the cumulative distribution function, F(s), of the fiber strength in a layer is doscribed by the Weibull distribution
F(s) = I • exp( -a(slsf,>b},(6)
where a, So and b are the distribution parameters. s is theapplied stress. It is supposed that each fiber in the layer canbe broken only once as the load applied to the composite isincreased.

3. Theoretical Calculations
One can theoretically calculate PL values from the de~sity distribution function v(n). Consider the equation for n*

..

..

J

J

nv(n)dn = 0.5 nv(n)dn

nO

(4)

0

The total load carried by the layer, P, is related to thestress acting on unbroken fibers by the equationpes) = N s = Nn [I - F(s)]s(7)
where N is the current number of unbroken fibers in thelayer. (Here, each fiber cross section is taken to be one unitof area.)

The equation (4) means that the total amount of AE signals
in subvolumes with D>n* is equal to 50% of the total
number of registered signals. The integration in the lefthand side of equation (3) is over the subvolumes with the
maximum number of signals; therefore, their total volume
will be the minimum volume of a sample containing thisnumber of AE signals. Thus, we have=Jnv(n)dn

With an increase of the applied stress, the number ofundamaged fibers decreases; therefore P as a function of s
multiplied by N has a maximum. The stress Se' at which
this maximum is reached can be evaluated from the equation(8)dP(s)/ds =0 at s = sc'
The value Sc is usually taken as the most probable failure
stress: s. = So(abr 11b •DO

LP(se)(5)nO

where n* and v(n) are taken for a given stress s•.
One can see from equations (4) and (5) that for thetheoretical calculation of PL(s.) curve we need a model ofcomposite fracture in order to calculate the number of AE
signals in the subvolumes and the internal stress distribution function p(s) which determines the actual stresses in
subvolumes. For a model we take the one first introduced
by Rosen (1964).

Consider this model, assuming that there is an initial
distribution of stress concentrators within the sample. (Eachsection of the sample which we used for experimentally
determining the PL encloses several layers; nevenheless we
can make no special distinction between layers used for the91

theoretical model and sections used for experimental AE
measurements because in theoretical calculations we deal
with relative units.) Let the distribution of stress concentrations be p(k). and internal stress in a composite sample isdetermined by SiM = k sC' where sc is the external stress applied to the sample. We suppose that the number of AE
signals is proportional to the number of broken ~bers. That
is why as an equivalent of equation (4) we can writejjF(s)p(s)ds = 0.5 F(s)p(s)dss·=p(ka) p(k(ka» dk(Is)/dk.,
and therefore we havep(ka) I/(k...u - 1)[1 - F(kasc) - k. dF(k.se)/dk.J.

=

The probability density P(SiM) can be obtained fromp(k) in the same way, taking Is = sinl /se. (One should also
take into account the transformation of a region [I, km••l in
which the initial distribution p(k) is different from zero.)(9)

Figure 4 shows the function PLese) calculated for different distributions of fiber strength. The probability density of initial stress concentrations was taken in the form ofequation (3) with k...n = 1.7 and equations (9) and (10) havebeen solved numerically using the MATCAD program. The
threshold stress s, according to the experimental data presented in Fig. 2 was taken as 70% of the composite fiacture
stress. Figure 5 shows the value of PLQI.x as a function ofk...u for different spread of fiber strength variations, charncterized by different b-values in the Weibull distribution.

0

where pes) is determined for the given value of appliedstress SC. In the last equation F(s) is equal to the number offibers broken at stress s (in relative units). and p(s)ds is theprobability that stress within the range [~, s+ds) is acti~gon the cross section. From equation (9), It follows that In
the sections where the applied stress S>5* the number ofbroken fibers constitutes 50% of the total number of fractures. The relative volume of these sections is minimal,
because the number of broken fibers in a section is proportional to the applied stress and the applied stresses in these
sections are at maximum. Therefore, for PL value we can
write

..
J

PL(s*) = F(s)p(s)ds

One can see from the curves that the localization 00pends on the dispersion of fiber strength: the wider the distribution, the higher the localization. Comparing the theoretical curve with the experimental one presented in Fig. 2
one can see that the theoretical curve fits the experimental
one within the error limits almost everywhere except in theregion near the critical stress. (The best fit is reached forlemu = 1.7, and parameters of Weibull distribution of b = 9,
a = 0.0 I, SO = 3.7 GPa, Sf 0.7 s,,). The difference between
the theoretical and experimental values in this region can be
due to the fact that a composite fails as the result of crack
propagation at stress lower than the ones required for thefracture due to microcrack accumulation. as was supposed in
the model.

(10)

s·

Equation (9) gives the value of PL calculated in the casewhen only the sections subjected to above-threshold stresses
are taken into account; therefore equation (9) actually gives
the value of PL equal to the PL".u following the definitions
given in the experimental section of the present work. We
can compare the PL m• x calculated from equations (9) and(10) to the PL value measured in experiments using equations (1) and (2). In case the initial stress distribution ofstress concentrations within a sample is known one cancalculate PL theoretically as a function of applied stressusing equations (8) and (9), and (I) and (2). The only problem is that the initial distribution of stress concentratorschanges with the increase of applied stress because acc0rding to the model the fiber breaks are considered as additional
stress concentrators.

=

We can obtain also the approximate solution for PL
which is close to the precise solution in cases of the internal stress concentrations being high in comparison withstress concentrations introduced by fiber breaks at the loading of a sample. Usually the condition is satisfied in case ofnarrow distribution of single fiber strength (high b-valuesin Weibutl distribution) and large values of kmu•

Let us find the distribution of stress concentrations at
various composite cross sections as a function of appliedstress. From the condition of force equilibrium, it follows
that the total load carried by a sample cross section is thesame for any cross section. Thus, from equation (7) wehave
Sint [I - F(Sin,») = ksc'
where Sint is the actual stress acting on fibers. As the actual
coefficient of stress concentrations which accounts for both
initial stress concentrations and stress concentrations"acquired" due to the fiber breaks upon loading, ka = Sint/sc;
therefore. we can write k = ka [I -F(kasc»).

Let us expand the exponent in the Weibull distribution
into a power series according to a Taylor's theorem, andignore tenns above the second order. Thus. we have F(s) =a(s/so)b. Let us take the initial distribution of stress concentrators in the form of equation (3). Substituting equations(3) and (6) into (9) and after the integration, we have
S

*- "

co
-~C'

where leo = [(k.... ' - 1)/2]1/(1)+1). Therefore. equation (10) yields
PL = (lemu - Ieo)/(lemu - 1).
One can see that the last equation gives the maximum valueof PL. which is reached when the applied stress in all composite sections exceed st!. For the ascending part of thecurve from equations (l) and (2), we have

The rule of transformation of distribution functions is:92

0.3r--------------------.
a

5 0.25:0:
ctJ
N'mo 0.2bo'0 0.15

...
Q)

~ 0.1
~

ctJ

a. 0.05__l

O~-----_t:

o

0.2

0.4

0.6

0.8

1.0

Stress (in units of fracture stress)
Fig. 4 Theoretical PL(s.) curves calculated for CFRP in case the distribution of internal stress concentrations is rectangularwith lema. 1.7. Parameters of Weibull distribution characterizing the fibers strength are: (a) b 9. So 3,7 GPa, a=O.OI and(b) b 4.7. So 4.3 GPa. a 0.25.

=

=

=

=

=

=

0.6r-------------------..

r:: 0 5
0 .

:0:
ctJ
N

'mo 0.4

.2

'00.3
.!
CD
~

E 0.2
~

as

a. 0.1O'---------------------l
1

1.2

1.4

1.6

1.8

2

Coefficient of stress concentrations
Fig. 5 Maximal value of PL as a function of maximal value of internal stress concentrations calculated for CFRP. Parameters of Weibull distribution characterizing the fibers strength are: (a) b 9. So 3.7 GPa. a 0.01 and (b) b 4.7. So 4.3.
GPa. a = 0.25.

=

PL = PL mu [ I - (s, - s.) I s.(kmu - I)].
The approximate solution fits well with the precise one
obtained for b = 9 and gives higher values in comparison to
the precise solution obtained for b 4.6. The most interesting fact which reveals the approximate solution is that the
PL values depend on parameter b of Weibull distribution
and k.nu of probability density of internal stress concentrations. At the same time, parameters So and a in WeibuH
distribution which determine the absolute value of composite strength have little innuence on the PL values.

=

=

=

=

=

Figures 4 and 5 show that there are two main factors
innuencing the localization. At the low stresses, the local·
ization is due to the variation of internal stress concentrations in the sample cross sections. The dispersion of stressconcentrations is apparently introduced into the composite
during fabrication and can be considered as a technical factor. At the stress close to the critical stress, the second localization mechanism works. At a subcritical stress, thelocalization occurs due to nonlinear dependence of microfracture probability upon applied stress. This mechanism

0.3,.----------------------,
c:
00.25

:;

co

.~

(U

o
.2

0.2

'00.15

...

CD

CD

E 0.1
~

co

a. 0.05

01...------------------------'
o
0.2
0.4
0.6
0.8
1
Applied stress (in units of fracture stress)
Fig. 6 Parameter of Localization as a function of applied stress for CFRP with brittle matrix.

0.25r--------------------....,
c:

o
:;

0.2

co

.~

co

g 0.15-...~o 0.1
CDE~

co 0.05a.

Ol.------------------------J
1
0.4
0.2
0.6
0.8
o
Applied stress (in units of fracture stress)
Fig. 7 Parameter of localization as a function of applied stress for carbon/aluminumcomposites: (a) standard samples; (b) samples after the low temperature treatment.
can be considered as a physical factor. The nonlinear natureof localization is confirmed by the fact that the approximate
solution only reproduces the ascending part of the precise
solution for PL(s.) (part of the curve at applied stress lower
than the threshold stress), and gives a constant PL value fora stress higher than the threshold stress. This is because in
the approximate solution we have ignored terms above thesecond order in all the expansions.

els. Nevertheless, the study of AE localization in thesecases can provide important information about internal
stresses and details of a fracture mechanism. This information can be used for technological improvements in composite development and fabrication.
The model used in the present analysis only considers
fiber breaks during composite deformation. Besides fiber
breaks. the delamination andlor debonding on a fiber/matrix
interface can affect the composite strength. Experiments
have shown that these processes also affect the behavior ofPL(s.) curve.

4. Discussion
We have considered the fracture of unidirectional CFRP
with ductile matrix subjected to a uniform tension along thefibers. The fracture of many other composites is a moresophisticated process, which requires more elaborate mod-In Fig. 6 the PL(s.> curve for a composite with brittle
matrix is presented. The matrix embrittlement was reached94due to the excess of hardener during the composite fabrication. A developed splinter shaped fracture surface is charncteristic for such a composite. One can see that the presented
PL(s.) curve looks like a superposition of PL(s.) curves
observed in the case of a fracture of CFRP with ductile matrix. This curve can be explained in a following way:
• on the first stage the microfracture occurs in a CFRP witha brittle matrix the same way as in CFRP with a ductile
matrix,• at a certain level of the stress the delamination crack along
the fibers arises,• the delamination crack, when arrested, acts as a stressconcentrator in another cross section of lhe sample; thischange of internal stress concentrations initiates a jump on
the PL(s.),• then. microcrack accumulation continues in the composite
with new distribution of internal stress concentrations, etc.
until in cenain cross sections some critical conditions are

The examples shown in Figs. 6 and 7 demonstrate thatthe study of AE localization in composites during deformation can provide important information regarding the process of the material microfracture and thus evaluate the materials quality and performance potential under the stress.

5. Conclusions
The present paper shows what information regarding acomposite fracture mechanism can be obtained by multichannel AE registration technique.
In the applied aspect, we can evaluate internal stressconcentrations within a sample. It is important to underlinethat obtained in this case is the information about internal
stresses which cannot be measured by other non-destructive
techniques such as X-ray or photoelasticity. The infonnation about internal stress concentrations can be used for theevaluation of ultimate material strength and, also, for theprediction of a place of a macrocrack. In case the dispersionof internal stress concentrations is high, one can expect thatthe position of a macrocrack will correspond to the region
with the highest internal stress. This region should also be
the most active in AE. At the same time, in case the internal stress concentrations are low, the location of themacrocrack can be detennined by the factors other than local
stress concentrations. In this case there can be no simple
correlation between AE activity and the location of a 00.
structive macrocrack.

reached.
Figure 7 shows the PL(s.) curve for carbon/aluminumcomposites. The samples were fabricated by pressure stimulated impregnation of carbon fibers with nickel coating byaluminium alloy B-93. Curve (a) shows the PL as a function of applied stress for standard samples; the fracture
strength of the samples was 770 Mpa and the shear strengthwas 28 MPa. One can see that in this case the localization
occurs in accordance with the theoretical model. The ascending part of the curve is explained as due to the dispersion ofinternal stress concentrations and the descending part of thecurve is due to nonlinear dependence of microfractures probability on applied stresses.

The use of AE signal location allows to evaluate internal stress distribution at stresses lower than the failure
stress of the composite. This circumstance provides a powerful tool for nondestructive evaluation.

Considering the composite shear strength, one canmake the conclusion that the interfacial strength in thiscomposite is too high, which results in material embrittlement. In order to verify this conclusion the samples were
subjected to a short-time cooling in liquid nitrogen. According to general theoretical considerations the low temperature
treatment should result in intensive interfacial microcracking due to the difference in coefficients of thermal expansion for aluminum and carbon fibers. The PL(s.) curve forthe carbon/nickel coating/aluminium composites after low
temperature treatment of samples is presented in Fig. 7,
curve (b). The low temperature treatment resulted in theincrease of the samples strength to 1.4 GPa. This increaseof the strength was apparently due optimization of interfacial strength as the consequence of microcracking. One cansee that PL(s.) curve in this case is similar to the PL(s.)
curve obtained for CFRP. Comparing the curves (a) and (b)in Fig. 7, one can also observe that the maximum values of
PL correlate with the sample strength. This correlation is incompliance with the suggestion that the localization is affected by the inhomogeneity of internal stresses. The higher
the stresses, the higher the localization (correspond to lower
PL values). The increase of internal stresses results in composite fracture at a lower applied stress.

Another important factor which affects the localizationis the nonlinear dependence of microfractures upon appliedstress. It is this factor that explains the localization at thestress close to the fracture stress. The theory of this final
localization is still incomplete and more experiments are
required to provide information for analysis. Comparison ofexperimental curves of AE localizations with the theoreticalcurves calculated on the basis of one or another theoreticalmodel helps to better understand the fracture mechanisms ofdifferent materials.

Acknowledgment
The research described in this publication was madepossible in part by Grant J9E I00 from the International
Science Foundation and Russian Government.

References
B. W. Rosen (1964), ''Tensile Failure of Fibrous Composites," AIAA Journal, 2(11), 1985-199 t.
95

C. Zweben (1968), "Tensile Failure of Fiber Composites,"
AIAA Journal, 6(12), 2325-2331.
V. S. Krivobodrovand G. N. Gubanova (1989), "Localization of Microfailure in Fibrous Composites," Mechanika
Kompozitnnykh Materialov, (3), 437-443.
A. V. Gavrilin and V.S. Krivobodrov (1989), "Interface
state evaluation in carbon/aluminium composites by accoustoemission data," Interface boundaries, strength andfracture ofcomposite materials, Leningrad, pp. 188-193.

Investigation of Damage Development in Paper Using
Acoustic Emission Monotoring
Per A Gradin and Staffan Nystrom
Abstract

2. Theoretical

The acoustic emission behavior of paper is investigatedin connection with the change of initial stiffness of paper.
Initially, the decrease in the number of fiber/fiber bonds
was accompanied by no acoustic emission activity. The
acoustic emission was observed above 74% of the fracturestrain.

If it is assumed that the damage state is isotropic andhomogenous and that the ratio of the number of broken
fiber/fiber bonds to the number of fiber/fibe'r bonds in thevirgin paper, D, can be used to describe the damage state, it
can be shown that the elastic stiffness coefficients Ejjkl(D)are given by:

L Introduction
During uni-axial loading of a paper sample, it isobserved that the load-extension curve has a non-linear
portion. This non-linearity can be caused by the non-linear
material behavior of the fibers (i.e., "plasticity"), breakageof fiber/fiber bonds, micro-cracking in the fibers, etc. If aloaded sample is unloaded and reloaded, it can generally beobserved that the initial slope of the load-extension curve
has changed (decreased) compared with the first loading. If
it is assumed that the non-linear behavior of the fiber
material does not change the elastic stiffness (as isnormally assumed in metal plasticity), then it must be
structural changes within the paper that are responsible forthis degradation of stiffness.
It has been reported that during early and intermediatestages of loading, the breaking of fiber/fiber bonds is thedominant damage process. If it is assumed that the damage
is isotropic then one single parameter can be used todescribe the influence of damage on each stiffness
coefficient and the damage parameter can be taken to be theratio of the number of broken fiber/fiber bonds to thenumber of fiber/fiber bonds in the virgin paper. Assumingthat each change in the initial stiffness is attributable to theincrease in number of broken fiberlfiber bonds, then thechange in inititial stiffness can be directly related to theratio of broken to unbroken fiberlfiber bonds. Acoustic
emission study has been extended to the evaluation of
paper (Yamauchi, 1995) and provides the insight needed tounderstand the underlying mechanisms. In this report, westudied how the change of initial stiffness of paper isrelated to the acoustic emission behavior.
Received 25 August 1995. The authors are affiliated with Mid
Sweden University, 851 70 Sundsvall. Sweden. This is based on apaper that was presented at the Fifth International Symposium on
Acoustic Emission from Composites. AECM-5. Sundsvall.
Sweden.
Journal of Acoustic Emission
Volume 13, Numbers 3/4

J;jkJ(D) = (1 - D)EijkJ(O)(1)

It is now reasonable to assume that D is proportional to thesum of events I,ev, i.e.,
0= aI,ev(2)where a is a constant. Combining equations (1) and (2) willgive:

= I - aI,ev(3)
The above equations assumes that the loading is such thatan appropriate damage criterion is satisfied. If theassumptions made are correct, it should, when a tensile test
is performed, be possible to fit the total number of events tothe elastic stiffness degradation through:Ejjkl(D)lEijkl(O)E(D(E»IE(O)=I - a I,eV(E)(4)

where E is the strain.

3. Experimental
The samples were cut from handsheets with an area
weight of 65 g1m 2 made of bleached soft wood kraft pulp
and with a nominal fracture strain equal to 3%. Specimen
dimensions were 18 mm width and 50 mm length with 5
mm each for the grip.
An MTS servohydraulic testing machine was used forthe loading and pneumatic grips were used for clamping of
the specimens. During the tests. the total number of events.
amplitude distribution and load versus extension, wererecorded.Two loading schemes, defined in Figs. I and 2,
were utilized in the experiments. They are referred to as
sawtooth and ramp loading, respectively.
The sensor used in the measurments had a resonancefrequency of 300 kHz and was placed in the center point of
the specimen. The threshold value was set to 40 dB inreference to 0 dB at I JlV at the sensor.

0730-oo50I9S/SS.00I1 3097-1 00
Copyright@l99SAcousticEmissionGroup

1% J of nominal fracture strain1%) of nominal fracture strain

100

Strain rate: 1.O%/minute
80

60

40

20
o~-....--.--.......---.---.....---.--..--~
Time

Time

Fig. I Sawtooth loading

Fig. 2 Ramp loading

In Fig. 3 is shown a typical load-extension curve
resulting from the sawtooth loading. The elastic stiffnesses
for the different strain levels are defined as the slope of thestraight lines A, B, ..., to E. In Fig. 4 is shown the elastic

stiffness for virgin specimens (nonnalized by the stiffness
from the first load cycle) as a function of the maximum
strain (in % of the fracture strain) in the previous loading
cycle. In the same figure, the strain e* is also shown atwhich acoustic emission was first detected. s denotes thestandard deviation of e*.

4. Results

Load

...

.

;

l
..,!:

i
:l

:

.:

;

;

.:

;/

..
,

...l

.

,

--+Extension~~~_e:;;",..:_~-.:.;._c:;....~'

Fig. 3 Load-extension curve for the sawtooth loading.
!l8Normalized Stiffiless

Normalized Stiffiless

•

1.0

0.8

I•

1.0

i

a!

•

0.6

•n•

I

Ii

Iiii

iii

•

0.8

"I .

•

I

0.6

0.4

c*- S

•

0.4

~*+ s

0.2

0.2

c*l

0.0
0

20

40

60

80

0.0 +----.~.....o20

100(% I of Frecture Strain........___,--.--.,_--"""T'"-....-_1
40

60

80

100

[%) of Frecture Strain

Stnin in Previous Load Cycle

Strain in Previous Load Cycle

Fig. 5 Degradation of initial stiffness for pre-strained
specimens

Fig. 4 Degradation of elastic stiffness.
Another type of test was also perfonned with the sameloading sequence. First a large sample was loaded to astrain level corresponding to 50% of the fracture strain andthen samples with the same dimensions as used before were
cut from the large sample and at right angle to the directionof straining. The similar data as in Fig. 4 is given in Fig. 5
for the pre-strained specimens. Figure 6 shows the average
stiffness values for both virgin and pre-strained specimens
along with standard deviations.

Normalized Stiffness

1.0--,,--..

..... - ....... ... - ..............
....

.. ----- .. ....-...
Pre - strained

0.9

Virgin0.8

0.7 -I---r---r--_.,._-_.,._--,----.----.--....,..-....,..--I
40
60
80
o
20
100

[%] of Fracture Strain

Strain in Previous Load Cycle
Fig. 6 Nonnalized stiffnesses for virgen and pre-strained paper.
99

Finally. virgin specimens were loaded according to theramp function defined in Fig. 2. The strain for the onset of
acoustic emission in this case was found to be 2.5 ± 0.3 %.
This should be compared to 2.2 ± 0.17 % for the sawtoothloading. implying a slight history dependency on the strain
for the onset of acoustic emission.

from Fig. 6 that the stiffness degradation is much less forthe pre-strained paper than for the virgin one, indicatingthat most of the fiberlfiber bonds are broken in the firstloading and that the 90° rotation of the load affects only asmall number of fiber/fiber bonds. Finally, we noted asmall dependency on the strain level for onset of AE, of theload history. In order to fully investigate the validity ofequation (4), precautions must be taken so as to make itpossible to lower the threshold value to such a value thatevery stmctural acoustic emission event can be detected.

5. Conclusions
For the virgin paper under sawtooth loading. it is foundthat at 80% of the fracture strain. the elastic stiffness has
decreased by about 20%. Assuming that equation ( I) holds.
this corresponds to a 20% decrease in the number offiber/fiber bonds as compared to the number of bonds in thevirgin paper. Up to the same strain level. there is no
acoustic emission activity with an amplitude larger than thethreshold value (40 dB) so that even far up as 80% of thefracture strain only 20% (weak bonds) of the number ofbonds in the virgin paper, has broken. It is also concluded

Reference
T. Yamauchi (1995), "Acoustic Emission as an Aid forInvestigating the Deformation and Fracture Mechanisms ofPaper". Proceedings of rhe Fifth lll/ernarional Symposium
011 Acoltsric: Emission from Composires. AECM-5. The
American Society for Nondestructive Testing. Colu mbus.
OH, pp. 129-138.

COVER PHOTOGRAPH
Fifth International Symposium on Acoustic Emission from Composite Materials was held July 10-14. 1995,
at Sundsvall. Sweden. About eighty participants gathered from 19 counu;es. including Russia for the tirst
time. The garden party of the Symposium was at the )9-ccntury mansion of a paper magnate. to which theparticipants were carried by a restored steam locomotive operated by local volunteers. In the photo (taken
by A. Maslouhi from Canada), CARP Chainnan Marv Hamstad is at the balcony. The weather during the
Symposium was excellent at 2S"C, but the photo below shows the organizers (from left to right. Staffan
Nystrom, Paul Howgate and Par Gradin) in their winter clothing at -2S"C.

100

12th International AE Symposium, Sapporo, Japan

Acoustic Emission Behavior during Plastic
Deformation of 8090 AI-Li Alloy
Ki-Jung Hong, Bee-Don Jeong and Chong Soo Lee
Abstract
Acoustic emission (AE) was measured during the tensile deformation of 8090 AI-Li alloy. The purpose of thisstudy was to investigate the AE source, and to correlate AE activity with the deformation mechanism of 8090 alloy
as a function of aging time, microstructure and tensile direction. Continuous AE near yield point showed amaximum at the initial aging stage and decremed with further aging. The decrease of continuous AE activity was
related to the change of deformation mechanism from planar slip to bypass. The continuous AE occurrence \sattributed to shearable a' precipitates acting as breakable pins for dislocation avalanche. Burst AE coincident with theload-drop of serration during post-yield deformation in under-aged condition was observed, and the source wasconsidered to be the localized deformation crossing a few grain boundaries through the slip plane work-softened byshearing of a' particles near yield point Tensile deformation of over-aged specimens in short transverse direction
showed a number of burst AE irrespective of serration. and an amplitude distribution of AE events showed thepossible AE source was rapid intergranular crack propagation.
1. Introduction

AI-Li alloys have attracted much interest due to their superior specific strength and modulus compared toconventional aluminum alloys. Such exc.ellent characteristics make these alloys as a promising candidate for future
aircraft structural materials. It has been known that although the increased strength of AI-Li alloys is attributed toprecipitation of 0' (AIJLi) particles. the a' precipitation also lowers ductility due to the strain localization and theformation of precipitate free zones (PFZs) (Luo and Youdelis, 1993). In recent years, research on AI-Li alloys hasconcentrated on improving ductility and toughness in two alloy system; the ternary AI-Li-Cu alloys (2090 type) andquaternary AI-Li-Cu-Mg alloys (8090 type) (Gregson and Harris, 1986). As a result, it has been found that one of theefficient methods is to introduce incoherent secondary precipitates such as S' phase in the matrix.
Regarding the AE behavior of these alloys, earlier investigations have reported that AE signals are largely
affected by the aging time and precipitation phases present (Roman et at., 1985; Sakamaki et at., 1990). However, it
is not fully understood yet as to how the AE varies with the microstructure and plate orientation. In this study,
acoustic emission has been monitored during the monotonic tensile deformation of 8090 alloy. We investigated the
AE source, and correlated AE activity with deformation mechanism of 8090 as a function of aging time.
microstructure and loading direction.

2. "Experimental Procedures
The 8090 alloy used in this work was supplied as the rolled plate of 45 mm thickness in the solution heattreated, 6% stretched and naturally aged condition by Alcan International Ltd., U.K. The nominal composition of thisalloy is shown in Table I. The as-received alloy showed typical pancake-shaped unrecrystallized grain structure along
the romng direction (Fig. I).

Received October 20. 1994. K.-J. Hong and H.-D. Jeong are affiliated with Research Institute of Industrial Science andTechnology. Pohang. 790-784. Korea and C. S. Lee is affiliated with Center for Advanced Aerospace Materials. Pohang
University of Science and Technology. Pohang. 790-784. Korea (cslee@vision.postech.ac.kr). Based on a paper that wasgiven at the 12th International Acoustic Emission Symposium. Sapporo. Japan and was included in the proceedings.
Progress in Acoustic Emission VII. JSNDI, Tokyo. Japan.

Journal of Acoustic Emission
Volume 13. Numbers 3/4

S61

073o.00S0I9S/SS.OOI13S61·S67
Copyright@1995Acoustic Emission Group

12th International AE Symposium. Sapporo, Japan

Table I Chemical composition of 8090 alloy used in this experiment (wt. %).
Element
Composition

Li
2.5

Cu

Mg

1.24

0.9

Zr
0.11

Fe
0.05

Mn
0.001

Si
0.017

Zn
0.04

Ti
0.022

Cr

0.002

Ni
0.006

AI
Bal.

T

Fig. I Three dimensional optical microstructure of 8090 alloy.

N. A. I. S. 4800
Data Acquisitor
and Analyser

Instron8501
TensionLoading

N. A. I. S. 4880
Signal Processing
Unit

x-v Recorder
CAMS)

Crosshead speed : O.2mm1min

Data aquisition ; load, position, strait)

Total amplifier gain: 40dB+3OdB

Threshold voltage : O.3V

Fig. 2 Schematic diagram of the apparatus for tensile and AE experiment.
In order to investigate the effect of aging time and microstruclUre on the AE behavior. two kinds of thermomechanical treatments were employed. One method was to perform solution treatment at 530·C for two hours. water

S62

12th International AE Sympo'sium, Sapporo, Japanquenched, followed by aging. This treatment reduces the stretching effect in the as-received alloy, and produces 0'phase as a major phase in the resulting microstructure, with small volume fraction of heterogeneously distributed S'
phase. The other method was to age the as-received material for obtaining homogeneous distribution of S' phasealong with &' phase. Both as-solution treated and as-stretched specimens were aged in fan driven air circulating ovens
for 0.5 to 64 hours at 190·C. Henceforth. the fonner heat treatment was designated as T6 treatment and the latter T8
treatment. Hardness test with aging time showed maximum value at 16 hour aging. Hereafter. 16 hour aging will be
described as peak aging, shorter aging as under-aging and longer aging as over-aging.
All tensile specimens had a dimension of 15 mm long, 6 mm wide and 3 mm thick at the gauge section.
Tensile tests were performed on an Inslron 8501 machine at room temperature at a crosshead speed of 0.2 mm/min.
and load-extension data were stored in hard disk for later use. The tensile tests were monitored using commerciallyavailable AE instrumentation (NAIS model 4000) with facilities for ringdown counting. event counting. andamplitude distribution. and nns voltage monitoring. The transducer was a resonant PZT ttansducer (NAIS model H2215) and was coupled to the polished specimen grip by a thin layer of grease under constant pressure. The gain
employed was 70 dB over a bandwidth of 100-300 kHz. A schematic diagram of the testing and AE recording system
is shown in Fig. 2.
Specimens for transmission electron microscopy (TEM) were electrolytically polished·.in 33% nitric acidmethanol solution at 12 V and -30·C. reM work was carried out on JEOL 4000FX andlor 200cX. Scanningelectron microscopy was also utilized for fractographic analysis.

3. Results and Discussion
The specimens tested can be divided into 4 groups; 2 groups by heat treatment (T6 and T8) and other 2 groups
by loading direction Oongitudinal and short transverse, L and ST. respectively). Typical stress-strain and rms voltagestrain plot is shown in Fig. 3 for T6 treated specimens loaded in the longitudinal direction. The as-solution treatedspecimen showed a continuous AE peak near yield point. This AE peak height increased at the initial stage of aging
time, and decreased with further aging. This trend of AE peak change. that is. initial increase and decrease with aging
time, can be considered to be related to the defonnation behavior of 8090 alloy.
In order to investigate the origin of acoustic emission at yield point. dislocation structure in the defonned gauge
section was observed by TEM for I hour aged specimen unloaded immediately after the AE peak was observed andrms voltage started to decrease. For comparison. microstructures of 64 hours aged specimen which produced no
acoustic emission peak (burst AE was observed) was also examined in the same way as mentioned above. Figure 4
illustrates the reM images, which show the change of dislocation shape from pair- to loop-type as 0' precipitates
become coarse with increasing aging time. Pair dislocation is the characteristic feature of planar slip deformation
mechanism. It is known that such coherent ordered precipitates as 0' phase lead to planar slip because 0' particles are
sheared by groups of dislocation pairs. on the same plane, to minimize the number of antiphase boundaries (APB's)
created by the leading dislocation of the pair (Gudladt and Schneider, 1992). Coherent, shearable precipitates arereported to become an AE source because they can act as breakable pins for dislocation avalanche (Heiple et al..
1981). This fact can be applied directly to the explanation of the AE peak in underaged 8090 alloy. As 0' grows
coarse and becomes non-shearable. deformation occurs by Orowan's bypassing mechanism and chances of AE
occurrence decrease because coarse &' cannot act as a breakable pin any more.
Additional important feature of this alloy is the distinguishable burst AEs in post-yield deformation (see Fig.
3(b». These burst emissions are coincident with the sawtooth like stress-strain curves (Fig. 5). Serration behavior in
Al-Li alloy is not well established. So far. it has been explained by the pinning of Li atom (Kubin et aI., 1992).
effect ofCu and Mg (Wert and Wycliffe, 1985) and shearable characteristics of 0' precipitates (Kumar and Mcshane,1993). We suggest that the formation of deformation band crossing a few grain boundaries through the slip planes
that had been work-softened by the shearing of &' near yielding leads to the serration phenomena and corresponding
burst emissions. This suggestion can be supported by the reM micrographs taken from the fractured specimen,
which shows the localized defonnation band (Fig. 6).
A convenient way of showing AE activity near yield is to plot peak nns voltage with aging time. Such a plot isgiven in Fig. 7, which shows 6% prestrain effect ofT8 specimen on AE activity compared with solution treated T6

S63

12th Intemational AE Symposium, Sapporo, Japan
500

T6

400

(a)
.5

300
200

100
0
500

0.0

(b)

400

.5

300
200

--..
as

Q.

:i
en
en

!

tn

100
0
500

0.0

(c)

400

.5

300

----

>

tn
:E

200

Q:

100
0.0

0

500

(d)

400

.5

(e)
.5

+.-...........--..--..-r-..--.--.-.......--r-..-..--...-......-r--..--... O•O
o

10

5

15

Fig. 3 Variation of AE RMS voltage and stress vs. strain with aging time for T6 specimen loaded in longitudinal
direction. (a) as-solution treated (b) 0.5 (c) 4 (d) 16 (e) 64 hours aging.
specimen. This figure clearly illustrates that T6 sample gives more emissions than T8 specimen. The low emission
activity of T8 specimen can be attributed to "Kaiser effect" caused by the 6% stretching although natural aging
during storage and shon period of artificial aging make weak emission reappear. In addition, it is possible that the
introduction of non-shearable S' precipitate contributed to lowerjng emission activity.
No clear effect of loading direction on acoustic emission behavior was found by the rms voltage monitoringalone. This result means that the deformation behavior is not strongly affected by the loading direction. An
amplitude distribution of AE signals during post-yield deformation showed some differences between L and ST
loading for over-aged specimen (Fig. 8). As expected by the pancake-shaped grain structure of the alloy, SEM imagesof fractured surface of L and ST loaded specimen showed typical transgranular and intergranular fracture. respectively(Fig. 9). Tentatively, the source of high amplitude ponion of AE signals in ST loading appears to be rapid
propagation of intergranular crack.

S64

12th International AE Symposium, Sapporo, Japan

Fig. 4 TEM image of precipitates and dislocations obtained from the specimen unloaded immediately after
continuous AE activities decrease. (a), (c) I hour aging and (b). (d) 64 hours aging.

-

400

as
a.

-=

.5

~

...
tn
!

->

tn

~

350

0.0

300
9.0

9.5

10.0

Strain(%)
Fig. 5 Dynamic strain aging with attendant AE from 8090 aged at 190°C for I hour in '1'6 condition.

4. Conclusions
Continuous AE ncar yield point showed maximum at the initial aging stage and dccrca..oo with further aging.
The decrease of continuous AE activity was related to the change of deformation mechanism from panicle shear to
bypass. The continuous AE occurrence is attributed to shearable precipitates acting as breakable pins for dislocation

S65

12th International AE Symposium. Sapporo. Japan

Fig. 6 TEM images showing deformation band in fractured T6 specimen.

1.0-o-:[]

.8

-->
tIJ

.6

.

.4

:e
Q:
><
ca

:e

- - - : T8

.2

0.0
0

1

10

100

Aging Time(hour)Fig. 7 Variation of peak rms voltage in yielding region with aging time.

10000

10000

(b)

(a)
en

II)

t:CD ----------------------- CCD ---------------------->
w

Iii

.!

'0

----------~----------_.

'0----------------------

E
Z::s -------

.

0.1
1
10
100
Peak Amplitude(mV)

0.1

10

1 0

Peak Amplitude(mV)Fig. 8 Distribution of AE peak amplitude in over-aged specimens loaded in (a) L direction and (b) ST direction.

S66

12th International AE Symposium, Sapporo, Japan

Fig. 9 SEM fractographs of the specimen loaded in (a) L direction and (b) ST direction.
avalanche. Burst AE coincident with the load-drop of serration during post-yield deformation in under-aged condition
was observed. and the source was considered to be the localized deformation crossing a few grain boundaries throughthe slip plane work-softened by A' particle shearing near yield point. Tensile deformation of over-aged specimens inshort transverse direction showed a number of burst AE irrespective of serration. and an amplitude distribution of AE
events showed the possible AE source to be rapid intergranular crack propagation.

Acknowledgment
This work was carried out with the financial support of Research Institute of Industrial Science and Technology(RIST). Thanks are also due to Y. M. Rhyim and S.H. Park for the experimental assistance.

References
PJ. Gregson and SJ. Harris (1986), Proc. 3rd Int'! Al-Li Conf., cds. PJ. Gregson and SJ. Harris, Institute of
Metals, London, pp. 327-28.
H.J. Gudladt and 1. Schneider (1992), Mater. Sci. and Engr., A157, 161-168.
C.R. Heiple, S.H. Carpenter and M.l Carr (1981), Mel. Sci., IS, 587.
L.P. Kubin, A. Styczynski and Y. Estrin (1992), Scripta Metall., 26, 1423-1428.
S. Kumar and H.B. Mcshane (1993), Scripta Metall., 28, 1149-1154.
A. Luo and W. V. Youdelis (1993), Metall. Trans. A. 24A(I). 195.

I. Roman. K. Ono and C.H. Johnson (1985), J. Acoustic Emission, 4,5111-5115.
K. Sakamaki. K. Yoshida, H. Takagi and M. Yoshida (1990), JSME Int'I Journal, Series 1, 33,362-366.

I.A. Wert and P.A. Wycliffe (1985), Scripta Metall., 19, 463-466.

S67

12th International AE Symposium, Sapporo, Japan

Development Of Thermal Shock and Fatigue Tests ofCeramic Coatings for Gas Turbine Blades by AE
Techniquec. Y. Jian, Tatsuya Shimizu, Toshiyuki Hashida,
Hideaki Takahashi and Masahiro Saito
Abstract
An accelerated and simple thennal shock/fatigue test method is currently required in the development of thennal
barrier coating systems for advanced gas turbine blades capable of operating at increasingly high temperatures withimproved perfonnance. In this study, acoustic emission (AE) monitoring was used to detect the fracture process of
Zr02-based thennal barrier coating systems in thennal shock and fatigue tests. Cylindrical specimens of conventional
two layer coating and functionally gradient materials (FOM) were tested under the simulated temperature environmentof gas turbine blade. Laser heating method was employed to heat the specimens. To detennine an appropriate thermalload for testing method. four different heating/cooling cycles were used. Experimental results indicate that the delamination growth in the coating layers controls the thermal shock/fatigue resistance of the coating system. Furthermore,
it is demonstrated that the total energy of AE during heating and cooling cycles can be correlated with the delamination length for both the thermal shock and fatigue tests. Based on the correlation, the fracture process of thethermal barrier coating systems is examined, and a suitable thennal cycle was determined for an accelerated test
method. Finally, the application of the AE method is discussed in the development of thermal shock and fatigue
testing method for thermal barrier coating systems.
I. Introduction

It has been demonstrated that a higher operating temperature is very effective in improving the thermal efficiencyof gas turbine. Since the operating temperature has already been raised to the limit for heat-resisting Ni-based
superalloys commonly used in modem gas turbine blades, it is difficult to increase the operating temperature further.
Thermal barrier coating (TBC) technology with superior heat resistance has been developed for gas turbine blades.
The conventional TBC is a two-layer coating (non-FOM), but this method presents a difficult problem of the coating
spalling off the substrate at the leading edge of gas turbine blade. Recently, a new coating technique of functionally
gradient material (FOM) has been proposed to overcome this problem. In order to establish the coating technique, an
accelerated thermal shock and fatigue testing method needs to be developed that simulates transient thermal loads
identical or close to that expected in service.
In this study, a CO 2 laser heating method was employed to heat two types of cylindrical specimens with nonFOM and FGM coating. The cylindrical shape of the specimens simulates the curvature of the leading edge of gas
turbine blade. Acoustic emission (AE) monitoring was used to detect the fracture process of the coating. Based on theexperimental results, the application of the AE method is discussed in the development of thermal shock and fatigue
testing method for TBC.

2. Experimental Method
The geometry of specimen used in this study is shown in Fig. 1. Non-FOM coating was a two-layer system
consisting of a Zr02-8 wt%Y203 (PSZ) over an NiCrAIY bond coat, and FOM coating was a multi-layer coating
Receivcd October 20. 1994. The first four authors are affiliated with Research Institute for Fracture Technology, Tohoku
University, Aoba-ku. Sendai 980, Japan (hashida@rift.mcch.tohoku.ac.jp) and M. Saito is with Advanced Technology
Section, Rescarch and Development Department. Miyagi Prefectural Institute of Technology, Miyagi. Japan. Based on apaper that was givcn at the 12th Intcrnational Acoustic Emission Symposium. Sapporo, Japan and was included in theproceedings, Progress in Acoustic Emission VII. JSNDI. Tokyo. Japan.

Journal of Acoustic Emission
Volume 13. Numbers 3/4

0730·0050/95IS5.00/13S68-S74

S68

Copyright@1995AcousticEmission Group

12th International AE Symposium, Sapporo. Japan

Detail of A

Fig. I Geometry of specimen.

Non-FGM coating
FGMcoating
O.3SmmPSZ
75IJf,PSZ+2S%NiCrAIY O.lmm
5()%PSZ+Sll%NiCrAIY 1).lInm
25%PSZ+7S%NiCrAIY (I.lmm
U.lmm
NiCrAIY

PSZ
7S%PSZ+2S%NiCrAIY
SO%PSZ+50%NiCrAIY
2S%PSZ+75%NiCrAIY
NiCrAIY
SUS3114

Fig. 2 Schematics of cross sections of two types of coatings.
Ihennore. the thennal resistance of the FGM coating
was higher than the non-FGM coating. Substratematerial of the specimens was SUS304 stainless steel
whose thennal and elastic properties were almost thesame as the Ni-based superalloys. Schematics of thespecimen cross section of the two coating types areshown in Fig. 2.

Computcrcontrolled"y"lcmLa"Cr bcam----1

The two types of specimens were air plasmasprayed. Experimental equipment using a CO 2 laser (fullpower 500W) is shown in Fig. 3. Impinging beam
diameter of the laser was 8 mm and the focal length was
200 mm. The output of laser power and irradiation time
were controlled by a computer-controlled system.

Specimen
Thc.rlllllconp/c- ~ClllllpUlcr

Dala
Loggcr~----------~

Fig. 3 Schematic of experimental setup for CO 2 laser
healing method.
system of PSZ and NiCrAIY. Compositions of themulti-layer in FGM coating were designed to have thesame oxidation resistance as that in non-FGM. Fur-

S69

The specimen surface was heated by the laser up \0
a predetennined temperature. After the temperature reached the predetennined level, the laser irradiation was interrupted and the specimen was then cooled. In order toinvestigate effects of heating and cooling rates on thefracture of the coating, fast-heating and slow-heating;natural-cooling and forced-air-cooling were used in the12th Intemational AE Symposium, Sapporo, Japanthennal shock and fatigue test. The falit-heating rate was about 3 times higher t~an lhe slow-heating rate, and lhe
forced-air-cooling rate was about 2.8 times higher than the natural-cooling rate. Combining the two heating rates
with the two cooling rates, we used four different heating/cooling lhennal cycles; Le., fast-heatinglnaturaJ-cooling(F.HIN.C) and slow-heatinglnatural-cooling (S.HIN.C), fast-heatinglforced-air-cooling (F.HIF.C) and slow-heating/forced-air-cooling (S.H/F.C). During a test, the temperature at lhe outer sur-face, Ts. and the temperature at lhe
inner surface. Ti. were measured using a pyrometer and a thermocouple. The AE activity in the fracture process ofthe coating wa.. monitored. using an AE sensor attached to the specimen substrate through a metallic block. The AE
monitoring was made with a gain of 80 dB. After testing, the specimens were cut at lhe irradiated portion. and lhe
specimen cross sections were analyzed by scanning electron microscopy (SEM) in order to evaluate lhe coating
damage.

3. Results and Discussion
SEM observations of damaged specimens showed two types of cracks in the coating; vertical crocks and delamination. Figure 4 shows SEM micrograph of the cross section (a) and the outer surface of the coating (b) with verticalcracks, which formed a network in the coating. Example of delamination damage is shown in Fig. 5.

§

00

00

Fig. 4 (a) SEM micrograph of cross section; (b) SEM micrograph of outer surface of FGM coating (specimen FA I
in Table J) which showed vertical cracks.

V~ \600.

l~hiknlY3 CI.n!

(/3!ICr\--.....~SNO
o

',SN
,""0
'-

o

srlll \

o

SN(D)

SN
0
Ff

0
SN

400

.fF

Osr

SN

o ....

SF
III

\ \

.... ....

.....

o

2()O

• • SNben';" nllll)

ClOO

51'

III

-----

soo

1000

Temperature on inner surface (Ti). ·C

Fig. 6 Thermal shock fracture maps of non-FGM coating. "SF": S.H/F.C; "SN": S.HIN.C; "FF": F.H/F.C;
No label: F.HIN.C; ..... : Furnace testing data.

Fig. 5 SEM micrograph of cross section of FGM coating (specimen FA4 in Table \) which showed delamination in interface.

S70

12th International AE Symposium, Sapporo, Japan

Using experimental results of the thennal shock tests, thennal shock fracture maps of non-FGM coating wereconstructed in a Ts vs. Ti diagram as shown in Fig. 6. The data with an asterisk on the line Ts = Ti was obtained
from a furnace testing. Similar maps have been reported by Ishikawa et aI. (1991) and Hashida et at. (1992). These
were obtained from thennal shock tests using a laser beam of 4 mm in diameter under the fast-heating and naturalcooling condition. Comparing two maps under the same heating and cooling condition, but with different laser beam
diameters, it is found that the critical temperature, above which the delamination occurred was higher for the 8 mm
laser beam than for the 4 mm laser beam. This result suggest that the local heating produces higher thennal stresses
compared to unifonn heating and gives a conservative estimate for the thennal shock resistance.
In the thennal shock tests of non-FGM materials, the two damage modes of vertical cracks and delamination
were observed in the case of the fast-heating cycles. However, no damage was observed in slow-heating cycles undersimilar conditions (Ts = I200°C, Ti = 600°C) for the same coating system. It may be explained that the compressive
stresses produced by the laser heating on the outer surface of the coating were smaller in the case of the slow-heating
than in the fast-heating (Hashida et aI., 1990). Thennal shock studies conducted on coating systems have shown thatthe compressive stress of high magnitude is the primary driving force for the eventual spallation of the ceramic coating (Evans and Hutchinson, 1984; Loh et at., 1986). The thennal shock fracture map (Fig. 6) shows that the range
of operating temperature of the advanced gas turbine (i.e., about Ts 1200·C, Ti 6Q0 C) is close to the conditionof the delamination obtained both for the 4 mm and 8 rom laser beam. Under similar thennal shock tests, FGM dii
not show any delamination under the temperature condition used, even though vertical cracking and distributed microcracking were observed to occur in some cases (Takahashi et aI., 1993; Hashida et aI., 1994).

=

=

0

Effects of the heating and cooling rate on the fracture of coating were examined by conducting thennal fatigue
tests. The results are summarized in Table 1. AE behavior observed in the fatigue tests are presented first. The AE
activity and the variation ofTs and Ti recorded in the thennal cycle are shown in Fig. 7(a) for the case where only
vertical cracks were observed. In the thennal fatigue test, the AE signals were recorded at me moment when the laser
heating was interrupted for every thermal cycle; for example, in Fig. 7(a), the sum of AE energy reconfed at the moment when the laser heating was interrupted, was 28.93 V2 and the energy amounts to 98% of the total energy recorded during all the thennal cycles. In contrast, the energy of the AE signals recorded during the heating and coolingprocesses was only 0.52 V2• It can be concluded that the majority of the AE energy resulted from the fonnation of
the vertical cracks, because the delamination of the interface was very small in this specimen; see Fig. 4(a).
2000
~

1600

10'
~

C! 1200 f-~
8e 800~F.H/F.C
151h cycle
Ts

2000

AE CounlS( Isec)•J-5. 10° >.
N

>.

e.o
<U

c

<U

400 ..

," .. ---

Ti

"!

.,

10" w

•

<

~ J600.

aC! 1200
e
8-

E 800

f!.

400

o ..._,-I_,-I_,-I"_.;:.~1.. .....J...._ .....
I ....... 10. 2
o J00 200 300 400 500 600 700o

S.H/F.C••f-lOCh cycle

:n
Ts

f--

....

o

•

AE CounlS( /sec)
1-5

•

1

.

.

.....,,
TI

.. "
I

I

100

200

"

... &...

.J

I

I

300

400

500

600

~

700

TIme. secTime. sec

00

M

Fig. 7 Temperatures on outer surface Ts and on inner surface Ti, AE energy vs. time (a) For specimen FA7 in Table
1, which was tested 15 cycles in the fatigue. (b) For specimen FA4 in Table 1, tested 10 cycles in the fatigue.
The delamination at me interface was observed in addition to vertical cracks (see Fig. 5), when AE signals wererecorded during the heating and cooling processes, as shown in Fig. 7(b). For this specimen, the AE signals werereconJed at the moment when the laser heating was interrupted from the 2nd cycle, and after the 5th cycle the AE
signals were recorded during the heating and cooling processes as well. The sum of AE energy recorded during theheating and cooling processes was 31.33 V2 and the energy amounts to 60.7% of the total energy recorded during all
the thermal cycles. The energy of the AE signals recorded when the laser heating was interrupted was 20.28 V2 • Tak-

S71

12th Intemational AE Symposium. Sapporo, Japaning the AE data into consideration, it appears that the AE energy of 31.33 V 2 resulted mainly from the delamination, while the AE energy of 20.28 V 2 corresponds to the vertical crack formation.
LJN in Table I represents the average rate of delamination growth. where Ld is the total length of delamination
observed on the SEM micrographs and N is the number of fatigue cycles. Comparing the values of LJN, it is foundthat the fast-heating (F.H) increased the damage of both types of coatings, in comparison with the slow-heating(S.H). The forced-air-cooling is also shown to increase the damage over the natural-cooling. Furthermore, LJN showthat the damage of the coating was the largest in the thermal cycle of F.HJF.C among the four different thermal cycles. In regard to the effect of the cooling rate on the fracture of the coating, the tensile stresses produced by theforced-air-cooling appear to be larger than those by the natural-cooling. Therefore, the thermal cycle consisting of thefast heating and the forced air cooling (F.HIF.C) is a suitable thermal cycle for an accelerated fatigue testing method.
In the thermal shock and fatigue tests, it was observed that the eventual destruction in both coatings was the spaJlation of coating, which resulted from the growth of the delamination.
From this AE behavior and the damage observation described above, it is possible to correlate the sum of AEenergy recorded during the heating and cooling processes in the fatigue tests with the length of the delamination
crack. The relations are shown in Fig. 8(a) for the non-FOM coating and in Fig. 8(b) for the FGM coating. It is seenthat there is a general correspondence for the two coating systems. For the non-FGM coating, the relation is ~proximately linear. In contrast, the relation is nonlinear for the FGM coating.
Table 1 The effecls of heating rate and cooling rate on the fracture of Non-FGM coating and FGM coating.
Modes ofSpecimen

Thermal

Tsmax

Cycle

FGM

t

°C

ThermalLenglh of In-

L,/N
E....;IN
terfuce Crack.
(mm/cycle) (V~/cycle)
Ld (mm)Cycle
Numbers,

FA7

F.II/F.C

1083

360

15

0.467

0.031

0.035

FAI

F.H/N.C

1247

414

10

1.707

0.171

0.036

FA9

F.H/F.e

1297

397

4

7.280

1.820

16.593FA4

S.H/F.e

1295

426

10

6.022

0.602

3.133

*FA2

F.H/F.C

1325

421

3

6.544

2.181

8.950

FA3

S.H/N.C

1202

479

10

1.512

0.151

0.120

FA5

F.HIF.C

1240

354

3

6.393

2.131

15.900*NFA5F.H/N.C

1248

468

2

7.613

3.807

7.920

*NFA6

F.H/F.C

1276

480

2

7.855

3.928

11.555*NFA8S.H/F.e

1253

495

4

7.213

1.803

5.845

FGM

Non-

Timax

"*" indicates that the coating was spalled.
50

50 _ - - - - - - - - - - - . . ,Non·FGM

•

FGM

40

40

'>

'>

~30

>'30-

~

~

g

~

••

u

w20

<

u
L\.I 20

<

10

2

6

8

10

12

......................--...................- .....

o~

14

0

Lenglh. mm

2

4

6

8

10

Length, mm(a) For non-FOM coating.
(b) For FOM coating.
Fig. 8 Total energy of AE vs. length of delamination.

S72

14

12th International AE Symposium, Sapporo, JapanSEM observations on the specimen cross section showed that the delamination in the non-FGM coating always
occurred just above the interface between the bond coat layer and the PSZ layer and the delamination in the FGM
coating always occurred close to two interfaces: the interface between the PSZ layer and 75%PS7J25%NiCrAIY layer
and the other between 75%PS7J25%NiCrAIY layer and 50%PS7J50%NiCrAIY layer. Because the delamination at
the interfaces is associated with the AE activity the linear relation between the AE energy and the delamination
length for the non-FGM coating is expected to be linear as shown in Fig. 8(a). The mechanical properties of theinterfaces in the FGM coating were different from those of the interface in the non-FGM coating. Therefore, it appears that the different properties and location of the delamination caused the nonlinear relation for the FGM coating
as shown in Fig. 8(b). Allhough the data are different from each other in the heating and cooling rate and in thenumbers of thennal cycle, there is a correlation between the total AE energy and the length of delamination for eachcoating system. Thus, it is possible to predict the length of delamination quantitatively and non-destructively bymeans of the AE method in both the thermal shock and fatigue tests. For example the EAEIN shown in Table I represents the average AE energy per thennal cycle and the same result can be obtained using the parameter EAEIN instead of the parameter LJN in evaluating effects of the heating and cooling rate.

4.

Conclusions

Thermal shock and fatigue tests via laser heating were conducted on the non-FGM and FGM coating systems
employing an AE method. For the fatigue tests the effect of heating and cooling rate was examined to identify thesuitable thermal cycle for an accelerated test. The conclusions obtained in this study can be summarized as follows:I) Thermal shock fracture map of the non-FGM coating was constructed using laser beam of 8 mm. In comparison
with maps obtained using a smaller laser beam (4 mm) it was shown that the critical temperature of the delamination
was higher for 8 mm laser beam than that for 4 mm laser beam.

2) The fast-heating increased the damage of the two types of coatings compared with the slow-heating. The forced-aircooling also increased the damage of the coatings compared with the natural-cooling. Therefore, the thermal cycle ofthe fast heating/forced air cooling was judged to be suitable thermal cycle for an accelerated fatigue testing method.
3) There was a correlation between the total AE energy and the length of the delamination. Thus, it is possible topredict the length of the delamination in the coating quantitatively and non-destructively by means of the AE
method.
References
A.G. Evans and J.W. Hutchinson (1984), "On the Mechanics of Delamination and Spalling in Compressed Films",
Int. J. Solids Struct., 20(5), 455.
T. Hashida and H. Takahashi (1990), "Laser Irradiation Thermal shock and Thermal Fatigue Test Procedure", Proc.
1st Int. Symp. on FGM., Oct. Sendai, Japan, pp. 365-373.
T. Hashida. T. Ishikawa, T. Tobe and H. Takahashi, (1992), "Development of a Laser Heating Method for Evaluating Thermal ShocklFatigue Resistance of Ceramic Thermal Barrier Coating for Gas Turbine Blade", Trans. Jpn. Soc.
Mech. Eng., 58(545), 15-19. (in Japanese)
Toshiyuki Hashida. Hideaki Takahashi, Tsuyoshi Ishikawa, Katsuhiko Takahata, Akira Kawasaki, Ryuzo Watanabe,
Koji Fujii and Motoi Kanazawa (1994), "Burner He1\ting Method for Determining Thermal Shock Resistance of Ceramic Coatings for Gas Turbine Rotor Blades". Advanced Materials '93. IIIIB: Composites. Grain Boundaries aOO
Nanophase Materials, cds. M. Sakai, M. Kobayashi. T. Suga, R. Watanabe, Y. Ishida and K. Niihara. Elsevier B.V.,(Trans. Mat. Res. Soc. Jpn., vol. 16B), pp. 1291-1294.
T. Ishikawa, T. Tobe, T. Hashida. H. Takahashi et.al (1991), "Evaluation of Thermal Shock Resistance of Zirconia
Coating for Gas Turbine Moving Airfoil by Laser Heating Method". J. Jpn. Thermal Spraying Soc., 28(4), 1-6. (inJapanese)

S73

12th International AE Symposium. Sapporo, Japan

R.L. Loh. C. Rossington and A.G. Evans (1986), "Laser Technique for Evaluating Spall Resistance of Brittle Coating". J. Am. Ceram. Soc., 69(2), 139.
H. Takahac;hi, T. Ishikawa. D. Okugawa and T. Hashida (1993). "La-;cr and Plasma-Arc Thermal ShocklFatigue Fracture Evaluation Procedure for Functionally Gradient Materials n. 711ermal Siwek and Thermal Fatigure Behavior
of Admnced Ceramics. Proc. the NATO Advanced Research Workshop on Thermal Shock (Nov. 8-13, Munich,Germany 1992), eds. Schneider and Gunter Petzow, Kluwer Academic Publishers, pp. 543-554.

Professor Hldeaki Takahashi (1940-1995)
Dr. Hideaki Takahashi. professor at Research Institute for Fracture Technolgy.
Tohoku University, Sendai. Japan. passed away in December 1995. He has been amember of the Tohoku faculty since 1968 and was promoted to a professor in
1981. He was the director of the Institute from 1981 to 1993.
He has been active in acoustic emission research since 1979 and published over
one hundred articles on AE and its various applications. about a half of them inEnglish. His 1981 paper on the AE-fracture study of 4340 and A533B steels inExperimantal Mechanics is perhaps most notable. but his group hac; made numerous contributions on composites and brittle solids in recent years. He wasone of the organizers of the 7th and 10th Intcrnational AE Symposia in Zao(1984) and Sendai (1990).

874

12th International AE Symposium, Sapporo, Japan

Fractals on Acoustic Emission during HydraulicFracturing
Ken-Ichi Itakura, Kazuhiko 8ato, Koji Nagano and Yasufumi Kusano
Abstract
In geothermal field study. AE (acoustic emission) method was employed to evaluate the artificial crack geometry
initiated by hydraulic fracturing. In order to improve this evaluation method. it is important to identify the spatial
and time series characteristics of AE activity during hydraulic fracturing. If the influence of latent natural cracks on
the fracturing pattern and on the AE generation process could be clarified. the precise evaluation of the artificial crack
would be possible.
To shed light on these problems. fractal property of AE activity during hydraulic fracturing of a rock specimen
was investigated in laboratory. Hydraulic pressure was applied to a drilled hole located at the center of the cubic rockspecimen (20 x 20 x 20 em) under different stress conditions. AE was monitored using a 6-channel system (lQ0-400
kHz) during the increase of hydraulic pressure until breakdown was observed. The distribution of AE source location
taking the relative AS energy into account indicated a fractal property. Also. the time series of AE count was fractal.
These results suggested that the fractal dimensions of spatial distribution and time series of AE are effective
parameters to evaluate the artificial crack initiation during hydraulic fracturing.

1. Introduction

Fractal analysis has been applied to various problems on rock mechanics (Xie, 1993). In panicular, the fracturesurfaces of rock, crack or pore distribution in rock, and fragmentation have been shown to be fractal; that is, thesestructures included self-similarity or scale-invariance. Also. acoustic emission (AE) from rock under stress indicatedfractal properties in the spatial distribution and in time series. For example, Hirata et al. (1987) revealed that thefractal dimension of AE source distribution in rock specimen changed with the inelastic defonnation process in acreep test. This result suggests that the fractal dimension of AE can be an indelt to predict the final rupture of rock.
In general, while fractal behavior was found in many phenomena related to rock mechanics, few reports haverelated the application of fractal characteristics to the in situ problems in the rock engineering field. In our study, we
consider the application of a simple parameter, fractal dimension, as the evaluation index of hydraulic fracturing ofrock mass. If the spatial distribution and time series of AE generated during hydraulic fracturing is fractal, it isimportant to investigate the relationship between the variation of fractal dimension and the fracture mechanisms.
In the geothermal area, the condition of latent cracks in subsurface rock mass is usually unknown. To grasp theproperties of the latent cracks is useful in controling artificial cracks. The artificial cracks may be characterized
precisely by means of an AE method. We expect that the AE source distribution and AE time series may be
dependent on the existence of latent cracks, and the fractal dimension of AE could be changed. If the fractal dimensionof AE during hydraulic fracturing is revealed. it will be an effective evaluation method for geothermal field in order to
eltplain the complex crack interaction.
As the first step, we examined the fractal dimension of AE produced during hydraulic fracturing of rockspecimens. In this paper, the experimental results and the fractal characteristics of AE activity in space and timeseries before breakdown will be described.
Received 20 October 1994.; in final fonn. 9 October 1995. The authors (itakura@epsilon2.csse.muroran-it.ac.jp) areaffiliated with Faculty of Engineering. Muroran Inslitute of Technology. Muroran 050. Japan. Based on a paper that wasgiven at the 12th International Acoustic Emission Symposium. Sapporo. Japan and was included in the proceedings.
Progress in Acoustic Emission VII. JSNDI. Tokyo. Japan.

Journal of Acoustic Emission
Volume 13. Numbers 3/4

073().OO5Ol951$5.00I13S75·S82

S75

Copyright (i)1995Acoustic Emission Group

12th International AE Symposium, Sapporo, Japan

2. Experimental Procedure

Two kinds of Welded Tuff (designated R and B) mined at Noboribetsu, Hokkaido, Japan were used after cutting
and grinding them to 20 x 20 x 20 em cubes. Figure I shows the configuration of the specimen, and some physicalproperties are in Table 1. Inner pressure was applied at the center of the specimen by using a hydraulic hand pump.
Figure I also indicates the location of AE transducers. Six AE transducers were affixed on the bevelled planes thatwere cut on the edges of the cube.
Figure 2 shows the suppon frame. During the hydraulic fracturing test, four venical planes of the cube specimen
were compressed with constant stress by hydraulic jacks as shown in Fig. 2. Figure 3 represents the whole experimental facility. Pressure data from the hydraulic pumps, 6-channel AE waveform data, and the waveforms to estimate
p-wave velocity were recorded on floppy disks through personal computers. The frequency response of the AE transducers (DuneganlEndevco S9204) was 100400 kHz, and total gain was 83 dB. AE waveforms were recorded with asampling interval of 1 JlS, and with 8 bit resolution. This AE monitoring system has been described elsewhere(Itakura and Sato, 1986; Itakura et aI., 1990; ltakura et al., 1991).
HydraUlic Pressure-"
Steel Pipe

.
·· .

I

·:I:.
··l....
·.
._--- JJ:.· .:.-..----'0 •I_'f--._._~'10

'0 •

__

o

- 0 -f-.

I
AE Sensor)AESenSa1~

C\I

i

~

II

t-

Silicone
RubberI
I(Plan View)(Front View)

200
(mm)

(Vertical Section)

Fig. 1 Configuration of rock specimen for hydraulic fracturing.
Table 1 Physical properties of rock specimens.
SampleType

Compressive
Strength
(MPa)

B

R

7.8
35.4

TensileStrength(MPa)

P-waveVelocity

S-waveVelocity

(mls)

(mls)

1.2
2.0

1580
2910

870
1260

Specific
Gravity

2.55
2.68

Table 2 Experimental conditions for 5 specimens.
Specimen
Rock TypeStress Condition
Stress Ratio
Loading Pattern

No.1

No.2

No.3

No.4

NO.5

B

R
Biaxial
0.25:0.25

R
Biaxial
0.25:0.12
I

R

Biaxial
0.25:0.12

R
Biaxial
0.25:0.12

Unconfined

I

n

n

12th International AE Symposium, Sapporo, JapanThe hydraulic fracturing test was carried out with two kinds of loading patterns. Figure 4 indicates the loading
patterns schematicalJy. One is a step loading pattern (I), and the other is the pattern of monotonous increase (ll). In
order to record as many AE waveforms as possible, the injection pressure rate was set low, approximately 0.1 or 0.2
MPaimin. Table 2 summarizes the experimental conditions for each specimen.
784

.

r

..._ .....~~_ Max. Pressure
15MPa(Plan View)
30 MPa (Max. Pressure 70MPa)
Max. Pressure 1SMPa

I

HydraUlic Jack

Support Plate

I(Vertical Cross Section)
Support Ring

(Plan View)
Fig. 2 Support frame for hydraulic fracturing.
Personal Computerr-------;I~= ¢; II( t~H..J
GP-IS

:25

Digital Oscilloscope§)
Pressure

I Transducer~~i1ft.t..A

Transmitter

Fig. 3 Block diagram of data acquisition system for laboratory experiment.

ST7

12th Intemational AE Symposium, Sapporo, Japan-~

1 or--------------....-~

10

Loading Pattern I
8 - --~

as0- s--r------t- --6 .---.- ••••• -.- •••••. - ~-Loading Pattern II

~

-

.J

Q)

6

:;:,

en
en

4

a..

2

Q)

Time

Time
Fig. 4 Loading patterns for hydraulic fracturing.

3. Experimental Results and Discussion

3.1 AE Activity during Hydraulic Fracturing Test
Figure 5 shows typical AE activities during a hydraulic fracturing test with the loading pattern II. Accumulated
AE events, AE count rate per second and injection pressure were plotted against time. It was found that the AE withrelatively small count rates were detected from the early pressure stage. After that, coinciding with the initiation of acrack at the bottom of the drill hole, AE events increased rapidly, and then reached the breakdown.

NOBORIBETSU WELDED-TUFF-4(R)
26 ~-------------------,...---r---,Total Gain 83dB
Breakdown Pressure 23. 23MPaC246min. )

24
22
20
18
........

cf

6.
~
='
~
Q)

e:t

140

........
00

120

Pressure

16
14

100

-0
C
ctI

X

UJ

Q)

60
40

4

20

~~~:h::tar;~:Idc;::::=jii~m::i¥=iltqI~

o

1

2

3

4

5

6

7

8

9

10

11

12

13

14

15

U)

+oJ

80 .......

10
8
6

-

X
.......

........
0

12

2

160

Events

C

Q)

>

-0

Q)

+oJ

+oJ

e:::

-<

+oJ

e
='
C)

to

c

~

0

u

ctI
~

C)

<

UJ

<

16 (xI03)

TIME (sec.)
Fig. 5 Typical result of AE activity with increase of injection pressure (specimen No.4, loading pattern II).
Figure 6 shows the result of AE source location corresponding to the experiment shown in Fig. 5. All AE
events detected during the experiment were mapped in this figure. Open circles imply the locations of AE events, andS78

12th Intemational AE Symposium, Sapporo, Japanzy... .. .... .
.
.. .,..-.
.- :. 0..•:-g ..
. . .'..
. ..
,.0 ••-.

0

.O'

0

e·

~

X

.'·0

~-+-~--~YX

0 100.0-80.0 (xlO ' )

....
.

•

0
0

0

d:r

80

0
0

80.0-60.0 (xlO' )60.0-4.0.0 (xl0' )4.0.0-20.0 (x 10' )20.0- 1.0 (xl0')
1.0- 0.0 (x 10' )oO· .ct)

o

. ..
. ito
.

...

~:

•

o

.

.0·..a .

..

..

.0

• 0

I

••

o

•

..

.... .

~

• ~

o

.0

o

z

.0

z

.. -. -.. ;.

o.

x+----'----~yFig. 6 AE source locations throughout the experiment for specimen No.4. Pressure: 0 - 23.23 MPa, Total events =1183. Noboribetsu Welded Tufftype-R.
their diameters indicate the relative AE energy. AE sources with smaller amplitude tended to spread throughout the
specimen from the early pressure stage. As one of the reasons for this scattering of small scale AB, it was speculated
that the porous structure of the specimen induced local microcracking. In addition, the error of AE source location
should be taken into account, because it became difficult to find the onset of waveforms for small-amplitude AE. On
the other hand, AE source with relatively large amplitude was concentrated at the bottom of the drill hole at thehigher pressure stage before breakdown. It was, therefore, concluded that these locations of AE with large amplitude
corresponded to the initiation of artificial cracks.

S79

12th International AE Symposium. Sapporo. Japan< No.4 >< No.4 >8

8~------------...,

Pressure 20.9-23.2(MPa)

7

6

6

-:a,4
5

....

Pressure 20.9-23.2(MPa)7501=0.046

'"-"

"C'
'"-"

:a,4

.Q

.Q

• 02=1.629

3

3

2

2

1

1

o

1

2

3

4

5

6

,7

8

01234

log(r)

Fig. 7 Fractal in the spatial distribution of AE.

*

678

log(r)
Fig. 9 Fractal in the spatial distribution of AE energy
volume.
Loading Pattern I
Loading Pattern nLoading Pattern I
Loading Pattern II* Breakdown Point

Breakdown Point.···No.1
O"·No.2...·No.3
D"·No.4,A···No.5

2
2

...

0

No·4.,D,.

D.···--_·····---.

No.4'"
iff

"~

III

o

1.5

1

o

10
Pressure(MPa)20

Fig. 8 Variation of fractal dimension against injection
pressure.

o

10

20

Pressure(MPa)Fig. I0 Variation of fractal dimension of AE energy
volume against injection pressure.

3.2 Fractal Dimensions ofAE
Fractal property for the spatial distribution of AE was analyzed by means of the box counting method (Feder.
1988). Figure 7 shows the relationship between the side length of box. r. and the number of box that contains an AE
source. N(r). In this figure. AE events detected preceding the breakdown in No. 4 specimen were analyzed. The relation was approximated by two-segment curves with the slopes 0, and O 2, This tendency to produce two-segment
curves was seen at other pressure levels. and in the other experiments as well. Taking notice at the slope O 2• it was12th International AE Symposium, Sapporo. Japan

found that the value of D2 varied with the injection pressure as shown in Fig. 8. On the contrary, D, was independentof the injection pressure. Although we cannot definitely conclude this independence. it is possible that the detection
limit of AE monitoring system causes the low inclination of the slope 0 1,
Using the sphere whose diameter is proportional to the relative AE energy, fractal behavior for the spatial distribution of AE spheres was also analyzed by means of the box counting method. Using the same AE data of Fig. 7, it
was confinned that the AE source distribution weighted by relative energy was fractal. as shown in Fig. 9. The fractal dimension of this case changed with the injection pressure as in the case of Fig. 8. In three of the five experiments with the loading pattern I. the fractal dimensions increased prior to the breakdown as shown in Fig. 10. However, with the loading pattern II, the fractal dimension did not increase rapidly before breakdown.
Using the sphere whose diameter is proportional to the relative AE energy, fractal behavior for the spatial
distribution of AE spheres was also analyzed by means of the box counting method. According to this analysis thefractal dimension estimated was dependent on the proportional coefficient of the diameter to the relative AE energy.
As shown in Fig. 9, it was confinned that the AE source distribution weighted by relative energy was fractal. In thisfigure the AE data of Fig. 7 excluding the events with small AE energy (less than 106 ) was used. so that the valuesof the fractal dimensions, O2 (for Fig. 7) and 0E (for Fig. 9) were not comparable to each other. Besides, the numberof data points to estimate the slope was different from that in Fig. 7. The fractal dimension, DE' obtained this way
also changed with the injection pressure as shown in Fig. 10. Comparing Fig. 10 to Fig. 8, the variation of D's
generally showed a similar pattern, with the exception of experiment No. I where O2 and DE behaved quite
differently. In the experiment No. I. high AE activity with large magnitude events was observed in the low pressurelevel. The high fractal dimension of the experiment No. I in lower pressure level of Fig. 10 reflected these transient
AE activity. In three of the five experiments with the loading pattern I, the fractal dimensions increased prior to thebreakdown as shown in Fig. 10. However, with the loading pattern II, the fractal dimension decreased or did notincrease rapidly before breakdown.
The above results show that the fractal dimension on spatial distribution of AE varies with injection pressurelevel, and depends on the loading pattern. Since the fractal dimension of AE source location reaches the level of over
2 at break down with the loading pattern I (Fig. 8), it was estimated that the spatial distribution of AE source
constitutes the plane which reflects the eventual fracture plane rather than the cloud composed by the points.
However, the spatial distribution of AE energy sphere considering the AE relative energy did not seem to be a planeshaped geometry as the fractal dimension reached only about 1.5. These results suggest that the fractal dimension of
AE source location will be useful to evaluate the geometry of artificial cracks. Furthennore, the fractal dimension of
the AE source distribution weighted by relative energy will be an effective parameter considering the magnitude of
AE events in each pressure level.
For the time series of AE, Higuchi's method (Higuchi, 1989) was applied. In this analysis. the variation of AE
count rate as a function of time was assumed as time series data. depicting the geometry of coast line. The sampling
rate of the time series was I second. Fractal dimension was measured by the calculation of coast line length.
Figure II shows a typical result for the data of experiment No.4. While an approximation with a straight line
was made in this case, two-segment curves occasionally fitted better for other data. The variation of fractal dimension
with the injection pressure is shown in Fig. 12. In three of the experiments. the fractal dimension increased abruptly
preceding the breakdown. This higher fractal dimension corresponds to the high fluctuation of AE count rate justbefore the breakdown. as seen in Fig. 5. Conversely, when the fluctuation of AE count rate detected by a transducer
was lower as the experiment No. 3 and No.5, the fractal dimension was decreased. Consequently, the fractal
dimension of AE time series could be regarded as one of the parameters to represent the fluctuation pattern of AE
count rate.
4. Conclusion
AE emanated during hydraulic fracturing test indicates the fractal properties in spatial distribution and time series
regardless of injection pressure patterns and stress conditions. Furthennore. it was found that the fractal dimension
varied with the injection pressure level. Especially, the fractal dimension of AE source location reflected the initiation of artificial fracture plane prior to breakdown in the case of loading pattern I.

S81

12th International AE Symposium, Sapporo, Japan

According to the results of our experiments, it was confmned that the fractal dimension will be a useful parameter to explain the artificial crack initiation in the geothennal field. Our next step is to conduct experiments forclarifying the relationship between artificial crack initiation and the latent crack in the rock mass.

< No.4 >Pressure 20.9-23.2(MPa)2*Loading Pattern I- - - Loadin Pattern II
Breakdown Point

*,
·,···
··

No.4 :

·

p

210

No.1

C>

.Q

,,
,
,,
,,•
,,
,,
,
,,

··

·
.
No.2
···
D--------- .
0o1log(t)

10

O~----'----'----'-~1O:--'----'----""'"""'"-2==O::-'-----.....J

Pressure(MPa)Fig. 12 Variation of fractal dimension of time series
against injection pressure.

Fig. II Fractal in the time series of AE counts.

Acknowledgment
The authors would like to thank Mr. O. Sakai for his assistance on the laboratory experiments. This work was
supported by a grant of the Ministry of Education, project No. 05232103.

References
J. Feder (1988), Fractals, Plenum Press, New York.
T. Higuchi (1989), "Fractal Analysis of Time Series", Proceedings of the Institute of Statistical Mathematics,
37(2), 209-233 (in Japanese).
T. Hirata et al. (1987), "Fractal Structure of Spatial Distribution of Microcracking of Rock", Geophys. J. R. Astr.
Soc., 90, 369-374.
K. Itakura and K. Sato (1986), Clustering and Migration of AE Prior to Main Faulting in Rock", Progress in

Acoustic Emission, 111, JSNDI, Tokyo, pp. 318-325.
K. ltakura, K. Sato and A. Ogasawara (1990), "The Observation of Microcracking Cluster in Stressed Rock by AE
and Seismic Tomography Techniques," Progress in Acoustic Emission. V, JSNDI, Tokyo, pp. 422-429.

K. ltakura, K. Sato and A. Ogasawara (1995), "Monitoring of AE Clustering Activity Prior to Main Faulting ofStressed Rock by Acoustic Tomography Technique," Proc. 5th Conf. on AEiMA in Geologic Structures m:lMarerials, Pennsylvania State University, 1991, Trans Tech Publications, Clausthal-Zellerfeld, Gennany, pp. 3-18.
H. Xie (1993), Fractals in Rock Mechanics, A.A. Balkema, Rotterdam.

S82

12th International AE Symposium, Sapporo, Japan

Acoustic Emission during Tensile Loading of Low
Velocity Impact-Damaged CFRP Laminates
Ob-Yang Kwon, Joon-Hyun Lee and Dong-Jin Yoon
Abstract
Carbon fiber/epoxy composite coupons previously damaged by low velocity impact were tested under static
tensile loading and the progress of damage was monitored by acoustic emission (AE). The degree of impact damage
has been correlated with the AE activity during monotonic or loading/unloading tensile testing. Special attention was
paid to determine optimal parameters of AE signals to characterize the microscopic fracture process of the composite
laminates. Rms voltage of AE signals ~uring the early stage of tensile loading was found to be an effective parameterto quantify the degree of impact damage. A newly defined parameter, integrity ratio, based on the rms voltage is also
proposed.

1. Introduction
Impact damage can be a serious problem in structures made of brittle materials such as composite laminates.
Polymer matrix composite laminates whose applications to aerospace structures are steadily increasing are likely to
be damaged by low velocity impact of various moving objects such as tools, runway stones, ice balls, and evenbirds. For the damage assessment and residual strength determination, various NDE techniques have been employed,either alone or in combination, such as ultrasonic C-scan. X-radiography. acousto-ultrasonics and acoustic emission.
Acoustic emission (AE) has been successfully applied to detect and locate the damaged area of impaet-damaged
composites during the subsequent quasi-static or low-cycle fatigue loading (Ghafari and Awerbach, 1986; Gorman.
1990; Ramstad et al.• 1992). They found that the severer the damage is. the more emission and the lower the stresslevel at which it initiates (Ghafari and Awerbach, 1986; Gorman. 1990). Although the impact damage is generally
nonvisual and was unable to be located during quasi-static loading, it could be easily detected and located under
tension-tension cyclic loading even within a few cycle (Ghafari and Awerbach, 1986). It was also found that long
duration events could be used to differentiate between stable and unstable behavior and to predict residual strength
when unstable behavior occurred. The normalized cumulative event rate moment and the average event rates are also
proposed to be a useful feature for the discrimination (Hamstad et ai., 1992). AE event duration distributions during
the initial load hold are. however. reported as independent of the degree of damage.
In this study. we have tried to find one or more optimal AE parameters for the damage assessment and theresidual strength prediction of low velocity impact-damaged composite laminates of carbon fiber reinforced plastics(CFRP).

2. Experiment
Specimens were cut from fully cured. autoclave-molded composite panels made with high strength carbon/epoxy
prepreg (RS1222. Toho Rayon Co.), which has elongation of 1.16%. Type-A specimens have stacking sequence of[±4S/0190}s and type-B specimens of [±4S]:!$ and their tensile strength are 803 MPa and 224 MPa, respectively. The
configuration and dimension of specimen with the position marked, at which the impact damage was introduced,
Received 20 October 1994; in final fonn. 8 August 1995. Oh-Yang Kwon is affiliated with Department of MechanicalEngineering, Inha University, Inchon 402-151, Korea (okwon@dragon.inha.ac.kr). Joon-Hyun Lee is with Dept. of
Mechanical Design Engineering, Pusan National University. Pusan 609-135, Korea and Dong-Jin Yoon is with Center for
Materials Evaluation, Korea Research Institute of Standards and Science. Taejon 305-600, Korea (djyoon@krissol.
kriss.re.kr). Based on a paper that was given at the 12th International Acoustic Emission Symposium, Sapporo. Japan andwas included in the proceedings. Progress in Acoustic Emission VII. JSNDI. Tokyo. Japan.

Journal of Acoustic Emission
Volume] 3. Numbers 3/4

S830130-0050/951$5.00113583-588
Copyright cg)1995Acoustic Emission Group

12th International AE Symposium, Sapporo. Japan·.
...................................
.................................
......................................
...................................
::::::::::::::::I~iI]~b::::::::::::::::::::.................................
................................
................................
...............................
.................................
1----.................................. 1

..
..

•

:::::::::·E:.:·1::'~····.·······:.·:.·.:.:.:.:.:.:.:.:.:. ·tlU·:-:LWJ:·:·:·:·:·:·:·:·:·:to::::::::::::::::::::::::::::::: 150---'------ 100

200

I Impact0.75~:=::===:~======~'~========:::==4==:~ 3
Fig. I Configuration and dimension of impact-damaged specimens.

are shown in Fig. 1. The degree of impact damage was adjusted by changing the impact velocity from 0.71 to 2.17
mls to be rated as 10%,30%, and 50% in reference to the total absorbed energy at fracture as 100%.

An electro-mechanical type Instron (Model 8162) was used under stroke control for monotonic loading and underload control for loading-unloading testing. The crosshead speed of 0.5 mmlmin was the same for all specimens understroke control whereas the loading rates were 1.28 kN/min and 0.27 kN/min for type-A and type-B, respectively. The
unloading points to obtain the Felicity ratio (FR) were 40%, 60%, 70% and 80% of the ultimate strength for type-A
specimens and 30%, 50%, 70% and 90% of that for type-B specimens.
A schematic diagram of the data acquisition system is shown in Fig. 2. An AE sensor with wideband response(WDIPAC) and a strain gage were attached on each side to the position closest to the damaged area. Detected AE
signals were amplified by 60 dB with 125 kHz to 1 MHz bandpass filtering and then fed into signal processors. The
intensity of AE activity was recorded by a true rms voltmeter (HP3400A) together with load and strain on a chart
recorder and on a computer. Threshold was set at 20 J.lV at the sensor. A microcomputer-based AE instrumentation(AET5500) was employed to collect the events and to extract the AE parameters. A number of digital wavefonns
were also recorded using a storage oscilloscope (LeCroy 9340).

DigitalInstronInstron host com uter§-lz.1s~ I
I ~~~!Estern

Strainamp.

au e

oscilloscope

AET 5500 system

busl

HDD

Signalprecessing

FDD

I-f- CEJI I HOD I

L....-1/-0

Phone--_.......

unit

(SPU)

PC

RMS
voltmeter

I Hard copy I
IX-V recorder \

Q-~

LJ~

Pream.

Fig. 2 A schematic diagram of the data acquisition system.

S84

12th International AE Symposium, Sapporo, Japan

3. Results and Discussion
3./ AE rms Vollage
Rms voltage of AE signals is a typical parameter recorded during most of AE experiments for its simplicity andreal time display. AE intensity in rms voltage during the monotonic loading was plotted together with load fordamaged specimens of both type-A and type-B as shown in Fig. 3. With the increasing degree of impact damage, theactivity during the initial stage prior to the major ply failure increased and the time for initiating the activity wasconsiderably shortened. The periods are taken as approximately up to 400 s for type-A specimens and up to 300 s for
type-B specimens, respectively. After these periods, regardless of the type of specimens, the baselines of the rms
voltage curve are starting to float and to show an upward slope. The activity during this period has been known as
the friction generated acoustic emission (Ghafari and Awerbach, 1986). The amount of the friction generated AE or
the AE during the initial stage of loading showed a close relationship with the degree of impact damage. Rms
voltage level was then taken as the indication of the onset of the friction generated AE activity and a newly definedparameter has been calculated in terms of the load level. This parameter will be discussed in more detail later in thissection.

_ 18.----------------.

18,....------------...,~ 16 Damage =1 0(%)
CD 14
C) 12

-

oS 10

~ 8
(/) 6
4

E
W

g

-e

CD 14

as 10

z

~

g8
(/)

W 2
«

---'...l.---I

100

200

300

400

500

eoo

6

E4

2 ~..:....,.;o:.;;..;.==...;=~"...

oDamage=10(%)-

OJ 12

~

« OL-"'--a._-'-_...I-_....I....-.;..__

16

00

700

_ 18 r-----------------.

500_ 18...---------------,~ 16

OBmage=3Dl")~ 16 Damage=30(%)-

C) 12

-

OJ 12

-14
CD

Q)

14

oS 10

.! 10

(/)

8-

(/) 8

E4

W

2 ~~~-.;;.J;JI-.lf;W'P"­

W

~ 8

~ 8

E4
«

00

100

200

300

« 2
400

500

SOD

00

700

ge =50{%r

-==..
z

g8

(/) 6

g 8
§

100

200

300

6
4

~ 2

2 ~.=--.~~WIU1~

00

~ 16
-14
CD
OJ 12
oS 10
f/)

E4

~

400

500

SOD

1500

_ 18.---------------,_ 18,...----------------.
~ 16-14
CD
OJ 12
Jg 10

500

oOt:.:......,J;..~-500~----1....000------'15OO

700

Time (sec)Time (sec)(a) type-A specimens(b) type-B specimens
Fig. 3 AE intensity and load vs. time during monotonic tensile loading.

S85

12th Intemational AE Symposium, Sapporo, Japan

3.2 AE Event Duration
Two representative AE events data with time (or displacement) from each type of specimens are shown in Fig.
4. Figure 4(a) from type-A specimen with 10% damage indicates much less AE events than Fig. 4(b) from type-B
specimen with 50% damage. Analysis with AE waveform parameters such as distributions of energy or peak
amplitude by events was also carried out. The results from the distributions itself, however, were not very useful todifferentiate the degree of damage.
When peak amplitude is plotted against event duration, AE signals from different states of materials or structuresoften can be differentiated. In Fig. 5, AE events during the initial period indicated as "analysis window" in Fig. 4
were analyzed by the cross-plot of peak amplitude vs. event duration. Typical number of signals analyzed were fromseveral hundred to several thousand. It is found that the increase in signal energy with the degree of damage accounts
not for higher peak amplitude but for longer event duration. Such a trend is more significant for type-A specimens
than type-B specimens. This is due to the stacking sequence and the type-A specimens are more vulnerable to impact
damage.
1888.,

588 _AI131ysis _Window(a)8
88:88:88

8B:11:12

EUEHTS us TInE FOR SEHSOR Z
HunBER OF IHTERVALS = 400
IHTERUAL SIZE = 3 (S)
10B8

(b)

58B

Al13Iysis

Window-o

BB:BB:oa

88:18:51

EUEHTS US TInE FOR SEHSOR Z
HunBER OF IHTERUALS = 4ee
IHTERUAL SIZE = 3 (S)Fig. 4 AE events vs. time during the monotonic tensile loading. (a) type-A specimen with 10% damage. (b) type-B
specimen with 50% damage.

3.3 Felicity Ratio vs. Integrity Ratio
Felicity ratio (FR) is defined as the ratio of the load at which significant emission restarts to the previously
applied maximum load. From a series of loading-unloading-reloading experiments, FR values were obtained for bothtypes of specimens with different degrees of damage. For both type-A and type-B specimens, undamaged specimen

SB612th Intemational AE Symposium, Sapporo, Japan90._.
-,.-...

·0

..

S)

S)

40

40
30

50

1ID

1s)

3S)

300

2S)

2llO

III

«Xl

4SI

SXl

-_

co '"

. '" .. -.. _---,..- -._--- _._.

10

,2 eo
Q.

l

--.

1SO

150

mI

250

aso

8lXI

4lllI

500

4SI

-dl

OI:IO

.... 0~~~~~~~ ~llD50_._...._..-.._ _
..

40
0

50

11111

150

2llO

.....

2Sl

-"

__

.....-_.-e~'"...._" .._...

_.. --..

0

50

100

150

2llO

250

8lXI

350

400

450

lIDO

0

SO

11111

15)

2llO

2SlI

3IlIl

3SlI

4lllI

4!iO

SlIlI

III

0 0
8
-0--- --0

- --0- ad

10

SXl

III

ODamage • 50('%)

III

450

SO{'l')

",'"

40

3D

«Xl

.. _--~-'"

~ eo
Q.

11111

35lI

8lXI

CD

i
50

2llll

a Damaga D

la 50

0

2llO

-g 10

:cr~------ .1::1

III

30

1ID

a:l

40

30

50

:s. 80 _.

la lilI

.:II:

0

_80

.. D8mllge .. SO{'l'):s. III
"C

III

0

--.-

30

0

• Damage .. 10(%)..

--_. ---.-.. _.. --...........

10

0

III

CD

_ _ • __ • ___ o _

80

10

CD

90

, Damage • 10('%)••••••

90

10

-

llD

-

Sl

,.

40

3IlIl

3SlI

4lllI

4SI

3D

SlIlI

Event duration (usee)

Event duration (usee)(a) type-A specimens(b) type-B specimens
Fig. 5 Peak amplitude vs. event duration of AE signals from the analysis windows.
and specimen damaged by 10% showed almost same values of FR. This implies that AE may not be an effective
tool for detecting small amount of the impact damage up to 10%. This was also the case when ultrasonic C-scan was
employed to examine the damage area with this specimen. In Fig. 6, FR values from each type of specimens areshown as a function of the degree of damage to compare with another ratio. The newly proposed one named"integrity ratio" has been defined as the ratio of the load at which a significant increase in rms voltage starts to theultimate failure load. It was so named that the ratio rapidly decreases with the degree of damage as shown in Fig. 6.
The ratio for type-A specimens decreases faster than those for type-B specimens. This is again due to the stacking
sequence and the higher strength type-A specimens are more vulnerable to the progress or accumulation of damages.
Although the definition of Felicity ratio looks quite simple and clear, practically it is not easy to determine the value
during or even after experiment. The integrity ratio can be obtained after the experiment and may be applicable only
for the damaged laminates as studied here but much easier to determine.

3.4 Residual Strength
The standardized method for evaluating the residual strength of damaged composites is generally known as CAl(Compression-Arter-Impact) test (NASA, 1982). AE activities were excellent parameters to quantify the degree of
impact damage and the residual strength of composite laminates when they were tested under compression (Ohsawa etaI., 1994). The compression test. however, consists of complicated fixtures and procedures and becomes an extremely
expensive method (Sjoblom and Hwang, J989). Therefore, the tensile residual strength was tried to be correlated withthe degree of impact damage in this study for its simplicity and cost-effectiveness of tensile tests. The result wasdisappointing in that there was no correlation between the degree of damage and the tensile residual strength. We
were also unable to correlate the residual strength with AE activity from the impact-damaged composite laminates.

SST12th International AE Symposium, Sapporo, Japan

0.9

-I-f

o.a _.
0.7

o 0.6.o::'&;~:--f--.--__.....

0.5>-:9- 0.4{f0.3..Type A

0.2 .- .Type B -. a Type A _0.1
oType B
oL:=:I:::::~..L....... ..............L.........................J......

o

10

20

30

40

....J
50

Degree of Damage (%)
Fig. 6 Felicity ratio and the integrity ratio with the fraction of ultimate load.
4. Conclusionsl) The analysis of AE signals from the initial tensile loading up to 50% of the ultimate strength can be utilized forthe assessment of impact damages in composite laminates.

2) Both AE rms voltage and signal duration data appeared to be useful parameters to evaluate the degree of damages.
3) A new parameter named as integrity ratio has been proposed as a useful index for the impact damage assessment ofcomposite laminates, which appears to be more efficient than the traditional Felicity ratio.

4) Although AE activity was clearly correlated with the degree of impact damage, we were unable to estimate theresidual strength of composite laminates under tension by AE monitoring.
References
S. Ghaffari and J. Awerbach (1986), Proc. 2nd Intern. Symp. AEfrom Compo Mat.• SPI, New York, pp. 120-124.
M.R. Gorman (1990),1. Acoustic Emission. 9, 131-139.
M.A. Hamstad, J.W. Whittaker and W.D. Brosey (1992),1. Compo Mat., 26,2307-2328.
NASA (1982), Spec. for Compression-After-Impact Test: Standard Test for Toughened Resin Composites, ST-l,
NASA Reference Publication 1092. Washington DC.
Isamu Ohsawa, Isao Kimpara, Kazuro Kageyarna, Toshio Suzuki and Akihiko Yamashita (1994), Progress in AE
VII, eds. T. Kishi, Y. Marl and M. Enoki, Japan Soc. NOI, Tokyo, pp. 511-516.
P. Sjoblom and B. Hwang (1989), "Compression After Impact: The $5,000 Data Point!", Proc. 34th Intern.
SAMPE Symp., SAMPE, Covina, CA, pp. 1411-1421.

S88

12th International AE Symposium, Sapporo, Japan

AE Characterization of Compressive Residual
Strength of Impact-Damaged CFRP Laminates
Isamu Ohsawa, Isao Kimpara, Kazuro Kageyama,
Toshio Suzuki and Akihiko Yamashita
Abstract
Acoustic emission (AE) characteristics were investigated in the compressive failure process of quasi-isotropic
carbon-fiber reinforced epoxy laminates with (+45/0/-45190)21 after subjecting them to impact damage. Impact load
was applied to a specimen by using a drop-weight impact tester, and the impact-damaged area of the specimen wasmeasured by ultrasonic C-scan method. The.applied impact energy ranged from O.5J to 5J. After the impact test,
compressive load was applied. Effects of applied impact damage, damaged area and dent of the specimens on the AE
activity were examined, and the residual compressive strength was correlated to the stress at which AE activity starts
to occur continually and the AE total events excluding those from the final fracture.

1. Introduction
Specific strength and stiffness are the driving forces to structural applications of carbon-fiber composites, thoughdamage tolerance is a major concern of reliability assuarance. Especially, the compressive strength of brittle composite sbUctures is reduced remarkably after impact loading, such as tool drops or low-speed foreign object impact(Jones and Baker, 1985; Caprino, 1984). Characterization of compression strength after impact (CAl) is important indamage tolerance design of the composite structure.

Pre-standardization studies have been conducted at NASA, SACMA, CRAG, Japan High Poly mer Center alii
other institutions (Anon., 1982; Anon., 1988a; Anon., 1988b; Anon., 1994), but effects of specimen configurationand impact loading conditions on the residual compressive strength have not been established yet.
In the present study, smaller specimens and newly developed compression test fixture are employed withacoustic emission techniques in order to understand the relation between failure process and impact damage.

2. Materials and Specimens
Laminates with (+45/0/-45190)21 were molded with T800/363l (0.14 mm/ply) prepreg sheet. The curetemperature of 3631-resin matrix was 182°C. Compressive test specimens were cut from laminated plates by
diamond wheel. The specimens were 150 mm long and 46 mm wide. In case of compressive test coupons oflaminated composites, standard test methods have suggested bonding of end-tabs for reinforcement of the gripping
area of the specimen. However, debonding between the end-tabs and specimen always occurs and this generates
meaningless AE under loading. In this experiment. therefore, the compressive fixture was designed with relatively
long gripping area and the specimens without end-tabs have exact parallel ends for loading unlike conventional
compressive specimens. This prevented AE generation caused by debonding of end-tab in the gripping area. This
proved to be a useful and easy technique providing specimen for AE measurement during the compressive test.

3. AE Instrumentation
Acoustic emission was detected by a single piezoelectric AE transducer (pAC Pico), attached 5 mm from an endof the grip on the center-line of the specimen. A standard pencil lead (JSNDI-006, 0.5 mm diameter, HB) recomReceived 20 October 1994; in final form, 22 September 1995. The authors are affiliated with Department of Naval Architecture and Ocean Engineering, Graduate School of Engineering, The University of Tokyo, 7-3-1 Hongo. Bunkyo-ku, Tokyo
113. Japan. Based on a paper that was given at the 12th International Acoustic Emission Symposium, Sapporo, Japan andwas included in the proceedings. Progress in Acoustic Emission VII. JSNDI, Tokyo. Japan.

S89

12th International AE Symposium, Sapporo, Japanmended by the Japan Society for Non-Destructive Inspection (JSNDI) was used to confinn adequacy of contact
between the AE sensor and the specimen, and also for sensitivity checking of the AE sensor. The AE instrumentation was Physical Acoustic Corporation (PAC) Locan-AT, filtered through a 40 dB amplifier with a 100 to 300
kHz bandpass filter. The threshold level of the AE system was 0.19 mV at the sensor. The sampling time and aMtime were set at 100 ms and I ms, respectively.

4. Experimental Procedures
Figure I shows a photo of the compression test
fixture, which was modified and developed from ourpast expe-riences of compression tests of glass fiber
composites. The fixture does not use any additional
device to prevent buckling of the specimen. The initialdead load due to the upper fixture is only 0.4 MPa, andthis effect is negli-gible. Effect of specimen length on
the compressive strength and failure mode without
impact damage was examined by changing it from 122
to 168 mm. The results are shown in Fig. 2. In therange of specimen length tested, it has remarkableeffects on the strength, as well as failure mode. In the
shorter specimen, the failure mode is symmetrical local
buckling induced by delamination in the mid-plane of
the specimen. In the longer specimen, typical Euler
buckling is observed. The transition is about 150 mmof total length. Gauge length of the specimen was,therefore, fixed at 50 mm in the follwing tests.
Fig. I Compression test fixture and AE sensor on thespecimen.
CIS

Q.

:i
.J£
0)
c

-

500

+

400

(

12

0

CD

>
u;

+

300

12

c.

E

t

~

(I)

200

0

()

100
120

.' )i:;)(::>:.:

+
130

140

150

160

170

Total Length of Specimen, mm
Fig. 2 Compressive strength versus total specimen
length with no impact damage.

~ ./_:~-::...."' ~~:+:t~;:(:·t/&~::::::;:: ::j :+.:'~; ;.::./):

Fig. 3 Spherical tip of drop weight of impact tester andclamping device for specimen.

Impact load was applied by using an instrumented drop-weight impact tester. A drop weight with a steel semispherical tip was used as an impacter. The total weight was 1.017 kg and the radius ohip was 8 rom. The specimen
was mounted between the supporting plates with cut-out holes as shown in Fig. 3. The diameter of the hole was 30
nun. The heights for the drop weight were chosen as 5, 10, 20, 30,40 and 50 cm, which correspond to 0.5, I, 2, 3,
4 and 5J of impact energy, respectively. An example of time history of acceleration data during impact loading isshown in Fig. 4. In the case of O.5J impact, the response was almost elastic and the energy may be lower than thelower limit of impact damage initiation.

12th International AE Symposium, Sapporo. Japan5z:lIl::

4

3

Impact energy

'tJ

ca

.9

0.5J

2
1

00.0

1.0

3.0

2.0

5.0

4.0

Time, msec
Fig. 4 Three examples of load-time history data during impact loading.

S. Results and Discussion

5./ Characteristics o/Compression after Impact

0.14

Strength
Depth of dent caused by an impacter drop was
measured by a digital linear gauge. Figure 5 indicatesthe relation between the drop weight height and depthof dent on the front surface of the specimen. The datashows a linear relation. In case of 0.5J impact, no dent
was observed, because the specimen only shows elastic
deformation.

e

E

.:
0.10
c
lD

Q

'0

i 0.05Q

The damage area was detected by using the immersion ultrasonic C-scan method with 10 MHz sensor after measuring the depth of dent. Figure 6 shows
the measured images of the damaged area, in which thereinforced fiber direction can be identified. The damage
area was measured precisely by using polar planimeter.

o
i

o

10

20

30

40

50

60

Height of Drop Weight, cm
i

1.0

2.0

i

i

3.0

4.0

i

5.0

i

6.0

Impact Energy , J

The relation between the depth of dent and damaged
area is linear as shown in Fig. 7. There are matrix
Fig. 5 Depth of dent versus the drop weight height.
cracks and bulge on the back surface, and the height ofthe bulge was at the same level as the dent depth. Figure 8 indicates the relation of the drop weight height amdamaged area. The correlation is linear up to about 3J impact. The damage area tends to saturate to the area ofcircular opening (7.07 cm2) in the impact test rig (see Fig. I), when the height is larger than 40 em.
Figure 9 shows relation between damaged area and CAl strength. According to the increase in damaged area, CAlstrength decreases along the second degree curve. If there is no influence of the cut-out hole in sup porting fixture,
the decreasing line can be estimated as going down linearly.

5.2 AE Characteristics o/CAl Specimen during Compression Loading
Acoustic emission from impact-damaged specimen were detected during static compression loading. Figure 10
shows the typical relation between AE event rate and time. The result is for specimen of 5J impact. There is no AE
activity during the early stage of loading, then AE activity is initiated (shown by an arrow in Fig. 10). Subsequently, AE event rate gradually increases, until it suddenly increases just before the final failure. Most of the tests
showed similar AE pauem as Fig. 10. The AE sensor, which was attached with instant glue on the specimen, cameS91

12th International AE Symposium. Sapporo, Japan

8 "T"'""------------.•...--..........

N

E
()

ci 6

•

!

<C
CD
0)

4

-

2

as
E
as

"D

()

•

as

Q.

- 0.00
E

•

I

....
0.05
0.10
0.15
Depth of Dent, mm

04l'-------r--....--~-_--.

Fig. 7 Impact damage area versus the depth of dent byimpact.

8.,.-----------_----.

C\I

E

••
•

()

as

!
ce:
CD
en
as
E

6

I

4

g

U
&

-

2

E

O+--e--r-...,.......,-...,.......,-...,....-r--.-....,..--,--I
o 10 20 30 40 50 60
Height of Drop Weight ,em

i

o
...

:-; .. :.:.::;;.:..;.:.:

I

1.0

I i i

I

2.0 3.0 4.0 5.0
Impact Energy , Ji

6.0

Fig. 8 Impact damage area versus drop weight heightand impact energy.

Fig. 6 Ultrasonic C-scan images of impact damage
area

off when the catastrophic final failure occurred. Consequently in order to analyze AE data of CAl test, the AE
characteristic was limited to the two points described below.
l. Stress above which AE events are continually generated. See the arrow in Fig. 10.
2. Total AE events excluding the sudden increase of AE events at the final failure.
I

Figure 11 shows CAl strength (squares) and the initiation stress of continual AE activities (filled circles) against the
impact energy. In specimens with no impact damage, there was a very small amount AE generated intermittently or
no AE activity until final failure. However, other specimens showed repeatable AE patterns similar to Fig. 10. 11lestress at the initiation of continual AE activity decreases linearly as the impact energy increases.
In case of low impact energy, AE was generated just before the final failure. In case of a 5J impact, the stress at
the initiation of continual AE activity is about 30% of the CAl strength. Figure 12 shows a good correlation

S92

12th International AE Symposium, Sapporo. Japan

300"T'-------------.

280~------------.

ClI
Q.

:e. 240

-...
-

200

-

J:

..c
en
c

en
c

QI

!

( /)

( I)

;(

100

:c

200

u

(.)

160+--.r.-_..,.-_...-_r-_ _--1
o
100
200
300

O+-----.--r----.......-..,....-..--~--.-~

o

2

4

6

8

Impact damage Area, cm

Stress at Initiation of Continuous AE , MPa

2Fig. 12 Relation between CAl strength and stress atinitiation of continuous AE.

Fig. 9 CAl strength vs. impact damage area.

aoo-y-

lee. 110.26..; ""58=: '1u.C8~e..................................
. .. .. . . . . ·................
··· ... ... ... ... ... · .. ..
8e ..... ·; .... :.•••. ;..... .; .... .: .... .
; .. :u .. : ..... : ..... 20..
.
. ··.................
. .
· .. .. ..
· . .
...............
· ,··. . .. Z.
~·................
·.· ... ...
;.... ;.... ;.... ; 10 "CIco0·................
..· ... ..
..J...............
···· .... .....
...............
· ... ...
8

U)

c
~

0

. 600

u

...U)

c
CD
>
w
'iii

400

0

w

<

-

·

8¥~z:::id~!!!t!!

.....

200

•

CD

Z

O..._--r----......--,----......--,--.__---t46oIPh 12 of 3 KITS ",. liKE (sec)a

246
Impact Damaged Area, cm2

Fig. I0 Typical relation between AE event rate, load
and time.

Fig. 13 Net AE total events versus impact damage area.

300 ~-------------,

280 ~-_-_-- _ _- _.....
ClI
Q.

~200

ClI
Q.

-e

..c
en
c

:s 240

•

u;

-...

..c
en
c
a.

-

;( 100
u

•

( /)

;(

D :CAI• : AE Initiation

O+---.-......,.-.....-.,.-......"""T'--.-,.--......---r~
o
10
20
30
40
50

160

Height of Drop Weight • em
i i i

o

1.0

2.0

200

u

0

i i i

3.0

4.0

5.0

200

400

600

800

Net AE Total Enents. counts

Impact Energy • J

Fig. 14 Relation between CAl strength and net AE
total events.

Fig. II Compressive behavior versus height of drop
weight and impact energy.

S9312th International AE Symposium. Sapporo. Japanbetween CAl strength and the stress at the initiation of continual AE activity, implying that CAl strength can be
estimated by this non-destructive method of detecting the initiation of continuous AE.
AE events, which occuredjust before final failure, appear to have no relation with the failure process. We define
the total event without the final AE activity as the net AE total event. Figure 13 shows a good correlation between
the impact damage area and net AE total event. In specimens with small damage areas, the net AE total event issmall. Figure 14 shows the relation of the net AE total event and CAl strength. When a small amount of net AE
total event is observed, the damaged area is small and the strength is high. The results indicate good correlations thatcan be used to supplement the stress at the initiation of continual AE activity.

6. Conclusions
Effects of impact energy on the dent depth, damage area and residual compressive strength is investigated experimentally with AE technique. The results are summarized as follows.
1. The compressive fixture used in this study is convenient to evaluate CAl strength for small specimens.
2. Compressive strength after impact has close correlation with impact energy, impact damage area and dent depth.
3. For damaged specimen, stress at the initiation of continual AE activity and total net AE events have close correlation to CAl characteristics.

Acknowledgment
The authors wish to thank Dr. A. Hamamoto and Mr. I. Chou of Ishikawajima Harima Heavy Industries Co.
Ltd. for providing the specimens.

References
Anon. (1982), Standard Test for Toughened Resin Composites, ST-l: Specification for Compression After Impact
Test, NASA Reference Publication 1092, National Aeronautics and Space Administration, Washington, DC.
Anon. (l988b), SACMA Recommended Test Method for Compression After Impact Properties of Oriented Fiber
Resin Composites, SRM2-88, Supplier of Advanced Composite Materials Assoc, Arlington, VA.
Anon. (1988a), CRAG Test Methods for the Measurement of the Engineering Properties of Fiber Reinforced
Plastics, Technical Report TR 88012, Royal Aerospace Establishment. UK.
Anon. (1994), Japan High Polymer Center, Report 6-1, Tokyo.
G. Caprino (l984),"Residuai Strength Prediction of Impacted CFRP Laminates", J. Composite Materials, 18, 508518.
R. Jones and A.A. Baker (1985), "Compressive Strength of Impact Damaged Graphite Epoxy Laminates", Composite Structure, 3, 402-414.

S94

12th International AE Symposium, Sapporo. Japan

Acoustic Emission Analysis on Interfacial Fracture of
Laminated Fabric Polymer Matrix Composites
Toshiyuki Denoya
Abstract
Acoustic emission (AE) technique is used to characterize the progression of interfacial failure during the defonnation of structural composite materials. Cyclic short-term flexure creep tests were perfonned on two types of plain
woven E-glass-fiber fabrics/epoxy laminate specimens. A new AE analysis method is utilized to recognize fracture
mechanism during a flexure straining and to characterize the evolution of interfacial fracture. Simultaneously. transmitted light microscopy was employed to examine the development and morphology of internal damage. A proposed
rising-slope criterion almost perfectly distinguished various source mechanisms of AE signals from laminated composites. The analysis of AE source mechanism is based on the criterion is capable to explain effects of loading pattern on the AE characteristics from the composites and also damage processes due to the stress-redistribution in thecreep test. The ratios of AE activity generated by a specific mechanism to the overall activity were introduced in order to estimate the failure progression caused during the test. The ratios were successfully used to evaluate different
damage progression of those specimens having different strand constructions but with the identical surface-treatment
on glass fibers.

I. Introduction
Much attention has recently been paid to the fiber/matrix interphase in composites, because this region canstrongly influence mechanical propenies of composites (Peters and Albertsen, 1993). In contrast with an interface.
the interphase has a cenain thickness. The properties of the material considerably vary between inside and outside of
the interphase. However, the thickness and mechanical properties of this interphase are unknown.
The single fiber composite test (Piggott. 1991) and the single fiber pull-out test (Desarrnot and Favre, 1991;
Chou et a!., 1993) have been employed for examining the fiber/matrix interface strength. The composite samples
used in these tests. however, are model materials. with very low fiber contents or with little restraint against matrix
material, and are significantly different from commercial composites. Moreover. woven fabrics composite laminates
are often utilized in various applications of fiber reinforced plastics. The fabric composites include undulation of
strands and inter-ply interfaces. which influence the mechanical behavior and fracture mechanism in the composites.
Consequently, these tests have limits and problems in the estimation of the inter-ply strength of commercial composites. In developing superior composites and fabricating reliable composite structures, it is important not only toassess the absolute strength (Netravali et a1., 1991; Manor and Clough, 1992) of the interphase in model materials
but also to evaluate the relative strength (Hamada et aI., 1991; Uenoya, 1993) based on nondestructive testing (NOnof the interphase in structurallarninates. To clarify detailed fracture processes in composite materials and to evaluate
the properties of interphase in commercial composites. new NDT methods have been proposed for this purpose (Wu,1990; Prosser and Hinckey, 1994).
The aim of the present investigation is to estimate the progression of failure processes and the damage accumulation during the defonnation of structural composites. In fiber reinforced composite materials, AE signals caused byseveral types of failure mechanisms are nonnally observed (Hamstad, 1986). Thus. it is required to interpret AE
events behavior during the defonnation and to distinguish the fracture mechanisms of the AE signals. Various analyses have usually been employed to identify AE source mechanisms. However, there is much room for devising a

Received 20 October 1994; in final form. 30 September 1995. The author is affiliated with Osaka Prefectural Industrial
Technology Research Institute. Enokojima, Nishi·ku. Osaka 550. Japan. Based on a paper that was given at the 12th International Acoustic Emission Symposium. Sapporo. Japan and was included in the proceedings. Progress in Acoustic Emission VII, JSNDI, Tokyo, Japan.

Journal of Acoustic Emission

Volume t3. Numbers 3/4

073()..()()5019SfSS.00I13S9S-S 102

S95

Copyright CI995Acoustic Emission Group

12th International AE Symposium, Sapporo, Japan

recognition algorithm in order to analyze all of the AE signals during a test. In this study, a simple algorithm, i.e.
AE source mechanism recognition by using the rising-slope of AE signals, was performed to distinguish different
micro-fracture mechanisms in laminated composites.

2. Basic Concept for Recognition of AE Source Mechanism
2./ Failure process in laminatedfabric composites

Three mechanisms of the micro-failure caused in laminated fabric composites by uniaxial deformation are (Sunet aI., 1989; Uenoya, 1988);(i) Matrix cracking; this occurs both in the resin-rich part in the matrix and at the points on the transverse strands
crossing over the longitudinal ones in the composites. The latter, especially at low strain, is observed as transverse micro-cracks appearing on the surface of materials at a regular interval.
(ii) Failure of the fiber/matrix interface; this includes the following;a) the fiber/matrix debonding due to normal stress to the fiber,b) the local delamination at the inter-ply interface, by straightening out fiber undulation in the straining longitudinal strands(iii) Fiber breaking; this is caused both by the mis-alignment of fibers and by initial defects dUJing material handlingin the fabrication process, and starts at the early stage of the deformation.
2.2 Rising-slope

Ve, the rate of the crack propagation caused in a solid, is in the range (Mott, 1948):
OS Ve S 0.38Vs (1 - CJC)"2,(1)

where Vs = -.J(EJP) is the sound velocity in a homogeneous solid, Co and c are the critical length of Griffith's
crack and crack length. respectively. A similar, but more complex, relationship is expected in a composite material.
Considering that Vs is determined by material constants such as Young's modulus E and the density p, Ve(i) is limited to a certain velocity range for each constituent material i of the composite material. Accordingly, it is assumed
that various crack propagation rates, with a certain distribution of crack length in the material i, are unique to eachspecific damage mechanism found in fiber reinforced resin matrix composites.
We can also presume that the crack propagation rate (CPR) during micro-failure process affects the leading edgeof AE signals; that is, the rise time 'tR' and the peak amplitude Vp, as shown in Fig. I. By combining the two, themean rising-slope (lR of an AE signal was defined as a representative parameter, (lR = VltR, where 'tR is the real risetime and has a value independent of monitoring threshold level.
Table 1 Material construction of the samples tested.
Prepreg

Laminated composite
NominalMaterial

Thickness

Count
(tex)
warp/weft

Densitystrandsl25nun
warp/weft

Weave

No. ofThickness

Laminae

(mm)

Fiber
fraction(wt%)

flexurestrengthaB(MPa)*F

0.22

67.5/67.5

~/S4

sarin

16

4

40.5

368

G

0.19

67.5/67.5

42/32

plain

22

4

65.7

369

I

0.22

135.0/135.0

20/19

plain

22

4

64.1

444

Reinforcement E-glass fiber (ESC21O); matrix: epoxy (Ep828+1001) + dicyandiamide; hot press condition: 1300 e,
1 hr; * 0"8 = Mltd 2, where M = maximum moment, t, d = thickness and ligament width of the specimen.

SI!l6

12th International AE Symposium, Sapporo, Japan

-t
Vp
I

Q)

'tJ

....:s-

e.

Vt

E

<I:

Time
Fig. I Definition of rising-slope of AE signals.

100

•

m
'tJ

..

C1

>

?at\etn

.. 80

CD

'\

+

.--:s'tJ

•

Q.

E

0

«

Fiber breakage
FIM Debonding,Delamination+ Matrix cracking

60

0

10

Rise time,20

lR, Jlsec

Fig. 2 Correlation between the rising-slope criteria and the frequency spectrum patterns of AE signals for Material G.

3. Experimental Procedures
Material systems of the tested samples were satin- or plain-woven E-glass fiber fabric/epoxy laminates as shownin Table I. These composites were fabricated using the same consolidation condition: at 403K (1300C) for 1 hour
under a constant applied pressure of 320 kPa. We used prepregs with different strand construction but employing an
identical silane coupling agent and concentration. The specimens were single-edge notched and 15 mm wide by 90
mm length. The notch length-to-width ratio (aIW) was 0.33, and the notch-root radius was 1.0 mm.
Edge-wise bending was applied to a specimen so that a tensile stress was generated at the tip of the notch. The
specimens were subjected to a series of stepwise loading with each load holding time of 600 s and increasing holdloads. We named this "a cyclic creep test" (Uenoya, 1992, 1994a). Under this loading pattern, we can expect the failure progression different from the one caused during monotonic loading.
The AE system used was a commercial AE processor unit (NF model 9640). AE transducers were attached toboth ends of the specimen. and the transducers used were of wide-bandwidth type (Nortec, DZ4lO-Hn. AE wavefooos were recorded by a transient recorder (Kawasaki Electronica modellMR90) with a sampling interval of 50 ns

12th Intemational AE Symposium, Sapporo, Japanand 2 k words x 8 bit data for each AE event. Conventional AE parameters such as amplitude and rise time alongwith the load were obtained by the AE processor. For further information about the test procedures, see Uenoya(1988, 1992, 1994a).

4. Results
4. J Rising-slope Recognition of AE Source Mechanism

The crack propagation affects the frequency contents of AE signals. The frequency spectrum analysis (FSA) by
FFI' (Fast Fourier Transform) has often been used for distinguishing source mechanisms of AE qualitatively(Uenoya, 1988; Suzuki et aI., 1990). AE signals from woven fabric laminates were classified into three patterns offrequency spectra by FFf (Uenoya, 1988), and the signals were identified with three specific failure mechanism cbscribed in Sec. 2.1. Figure 2 presents a correlation between the source mechanisms recognized by the FSA and therising-slope VrltR of AE signal for Material G. The points indicated by the same symbol appear in a certain region
divided by curves A and B presenting constant rising-slopes. This means that there is a rising-slope criterion (RSC)
to discriminate AE source mechanisms. The criterion, Le. the slope values of curve A or B, is experimentally determined. The rising-slope recognition analysis successfuUy identified over 80 % of analyzed signals, and over 90 %. in
particular, between fiber/matrix debonding and local delamination as shown in Table 2 (Uenoya, 1994b). The slope
values obtained from tested composite materials F, G, and I were practically identical for the curve A or B. This implies the existence of a criterion for distinguishing source mechanisms in different glass fiber/epoxy laminates tested.
Table 2 The ratios of AE events successfuUy identified by using the rising-slope criterion (RSC).
Materials

Matrix cracking

Debonding, delamination

Fiber breakage

F

0.80
0.80
0.81

0.88
0.85
0.92

0.75
1.00

G
I

0.77

A conventional type of AE analyzer, although easy to use, has a disadvantage giving the time error (~'t = t R t R') between the real rise-time (tR) and the apparent rise time (ta') of the signal above a preset threshold level. With
regard to the error, a correlation between ~t and the amplitude (Vp) of AE signals can roughly be determined. Accord-

ingly, simple recognition analysis of acoustic emission using the RSC was possible using a conventional AE analyzer, if preliminary tests were conducted on similar materials in order to obtain the criterion and the correlation of
M versus Vp' The data given in Fig. 2 was obtained by employing the real rise time from the leading edge of AE
signals with such a correction.
4.2 Evolution ofAE with Identified Source Mechanism

The following nomenclature is used:
E(M), E(D), E(F): cumulative AE energy due to matrix cracking, fiber/matrix debonding and local delamination, and fiber breaking
Em: cumulative AE energy, = E(M) + E(D) + E(F)Ne(M), Ne(D), Ne(F): cumulative AE events due to matrix cracking, fiber/matrix debonding and local ~lamination, and fiber breaking
Ne(T): cumulative AE events, = Ne(M) + Ne(D) + Ne(F)i (fracture mechanism): M = matrix cracking, D = fiber/matrix debonding and local delamination, and F =fiber breaking.
T: the sum of the three fracture mechanisms.
4.2. I Effect of loading pattern on failure sequence (AE characteristics)
Figure 3 indicates a typical evolution of AE events, shown with discriminated source mechanisms for Material
G excluding the final loading step. During a cyclic creep test, Fig. 3(a) demonstrates that the activities of Ne(D) continue to increase substantially after each load hold whereas Ne(M} and Ne(F) increased only moderately. This ob

S98

12th Intemational AE Symposium, Sapporo. Japan

1000....-------------.....,
Material j G
0.92
o Matrix cracking
750
El1I Debondlng, delamination

I!!iI Debonding, delamination

150

o Fiber breaking

500

250-r------------__.
Material j G
200
o Matrix crackingo Fiber breaking

100
0.75

(a)

250

o

o

050 ° .58
42
0.250.33°.
'

O+-~-O:-~~~

6000

4000

2000

(b)

50

°·67

0.23 0.34 0.46 0.57 0.68 0.79 0.91 0.98
Normalized load PIPs

Test time t, sec(a) During a cyclic creep test.
(b) During a monotonic loading test.
Fig. 3 Failure evolution estimated by the AE source mechanism recognition analysis for Material G.

3000 -r-------------""T"""""1
Material; Io Matrix cracking
2000

IITlJ Debonding. delaminationo Fiber breaking
PlPa=O.80
0.73
°·67
060

1000

o

Q.3304rP·~o

0.53 .

.

2000

4000

6000

8000

Test time t, sec
Fig. 4 Micro-failure evolution estimated by the AE source mechanism recognition analysis for Material I during acyclic creep test.
served activities of Ne(D) was more noticeable in a series of stepwise loading than in a monotonic loading shown in
Fig. 3(b). The Ne(D) dominated the evolution after a load hold. This may indicate that the fiber/matrix debonding andlocal delamination were induced by stress redistribution in a laminated specimens during the load holds.
4.2.2 Effect of material construction on failure sequence (AE characteristics)
As shown in Fig. 4, the distribution of these types of AE events evolved in the nearly same manner in Material
I as in Fig. 3(a) for Material G. Material I had a different strand construction but used the same surface finish. The
evolution of failure mechanisms in these two materials showed the following differences:a) The fraction of Ne(D) for Material G evolved more prominently than for Material I, from the beginning to theend of deformation.
b) A larger fraction of Ne(M) was detected from Material I than from the material G.
With transmitted light microscopy, the failure appearance near the notch expected from the above failure mechanism
evolution was confirmed in terms of the damage lone size and the number and size of transverse cracks. In Material
G, Fig. 5(a) shows that whitening (shown in dark bars) is caused by fiber/matrix debonding along the longitudinal

S99

12th International AE Symposium. Sapporo. Japan

G711F
c

~.

.~>" .

I792R,*50

~b)

r

L

2mm
Fig. 5 Failure appearance near lhe notch tip after tests (a) for Material G and (b) for Material I.
direction of a specimen, the debonding at the intersections of warp and weft fibers and fine transverse matrix cracks(TMCs). In Material I, Fig. 5(b) indicates many large TMes. fine longitudinal matrix cracks and local delamination.
However, it is not always possible to explain the interrelation among the fracture mechanisms on the basis of
the AE event evolution such as Figs. 3 and 4. To clarify the difference between the results from the two materials,
we introduced the following AE activity ratios:
event ratio of fracture mechanism i =E(i)lE(T)energy ratio of fracture mechanism i = Ne(i)INe(T).
The evolution of event ratios is shown in Fig. 6. The above differences are prominent between the two materials,
particularly in the early fracture stage. We can also find the differences between the two composite materials from8100

12th International AE Symposium. Sapporo. Japan

1.25-r-------------.,

--

1.25

CD

1.00

1.00

CD

0.75

0.75

0.50

0.50

0.25

0.25

Material; G

to-

~
:.
z

.-

0
:;::
fa

c

CD

>

(a)

(b)

Material; I

W

0.00

4000
2000
Test time t, sec

0

6000

2000

4000

8000

6000

Test time t, sec

Fig. 6 Micro-failure evolution with the AE event ratios (a) for Material G and (b) for Material I during a cyclic creep
test.

--w
=-

--

1.25

1.25

W

.

0

Material i I(a)Material; G

~

1.00

1.00

0.75

0.75

(b)
Matrix cracking
Debonding. delamination
Fiber breaking

:;::

as

..

>.

0.50

0.50
..
[]

C)
CI)

c

0.25

[J

0.25

w

~

0.00

0.00
0

2000

4000

0

6000

2000

4000

6000

8000

Test time t, sec

Test time t, sec

Fig. 7 Micro-failure evolution with the AE energy ratios (a) for Material G and (b) for Material I during a cyclic
creep test.
the appearance of the early failure behavior and the beginning of fiber breakage. Considering the material parametersand fabrication conditions, it was presumed that the observed differences originated from the geometry of weave aOO
fiber undulation as well as the diameter of reinforcement yarns. AE event ratios clearly identified the progression of
micro-fracture in terms of mechanisms.
The evolution of energy ratios is shown in Fig. 7. Here, delamination and fiber failure are much more dominant.
The fraction of E(F)IE(T) is larger in both materials than that of Ne(F)/Ne(T) shown in Fig. 6. Effects of delamination at the early stage are also shown to be greater. These indicate that fiber failure and delamination produce moreenergetic AE signals than the matrix cracking.
AE activity ratios clearly characterize the micro-fracture progression from the viewpoint of fracture mechanism
instead of damage level caused in laminated fabric composites. The energy ratio demonstrated the progression of fiber
breaking just before and after load hold.

s. Conclusion
An experimental approach has been presented to characterize the progression of interfacial failure in the overall
failure generated in structural fabric composites. This approach. based on the AE technique. depends on the determi

5101

12th Intemational AE Symposium. Sapporo, Japannation of AE signal features by the RSC, and the frequency spectrum analysis. To describe failure progression, theratios of discriminated AE signal features were inlroduced.
Based on the experimental results, the following conclusions can be reached:J. 11Je faiJure sequence can be analyzed by applying the RSC to all of the AE signals generated in a test. For a given
laminate, loading patterns affected the failure progression during defonnation. The failure during a cyclic shon-tenn
creep test includes more AE due to interfacial failure from stress-redistribution in comparison to the failure during
monotonic loading.
2. The analysis with the event ratio and the energy ratio of AE was able to show the influence of weave conslrUction
on fracture processes for two kinds of woven fabric laminates having different weave construction but with the same
surface-tteabnent on glass fiber. In particular, for the initiation and development of transverse matrix cracking, theresults obtained by optical and AE technique are in agreement

References
C.-T. Chou, U. Gaur and B. Miller (1993), 1. Adhesion, 40, 245-256.
G. Desarmot and J.-P. Favre (1991), Compos. Sci. and Tech., 42, 151-188.
H. Hamada, Z. Maekawa, N. !kula, H.lchihashi and E. Nishio (1991), Trans. JSME, 57A, 927-933, (in Japanese).
M. A. Hamstad (1986), Exp. Mech., 26, 7-12.
A. Manor and R. B. Clough (1992), Comps. Sci. Tech., 45, 73-8 I.
N.F. Mott (1948), Engineering, 165, 16.
A.N. Nettavali, Z.-F. Li and W. Sachse (1991), J. Mater. ScL, 26,6631-6638.
P.W.M. Peters and H. Albertsen (1993), J. Mater. Sci., 28, 1059-1066.
M. R. Piggott (1991), Compos. Sci. and Tech., 42, 57-76.

W.L. Prosser and J.A. Hinkley (1994). J. Mater. Sci. Lett., 13, 213-214.
F. Sun, M. Iwamoto, E. Jinen and M. Suzuki (1989), 1. Soc. Mat. Sci., Japan: Zairyo, 38,360-366 (in Japanese).

M. Suzuki, M. Imura, E. Jinen, S. Kida, M. Shinobu and Y. Miyano (1990), Progress in Acoustic Emission V,
eds. K. Yamaguchi et aI., Japan Soc. NOI, Tokyo, pp. 560-566.

T. Uenoya (1988), Progress in Acoustic Emission IV, eds. K. Yamaguchi et at., Japan Soc. NOI, Tokyo, pp. 679686.
T. Uenoya (1992), Progress in Acoustic Emission VI, eds. K. Takahashi et aI., Japan Soc. NOI, Tokyo, pp. 109116.
T. Uenoya (1993), Proc. 1993 National Conf. on AE, Japan Soc. NOI, Tokyo, pp. 163-168. (in Japanese).
T. Uenoya (l994a), Advances in Composite Materials, (CJMRI2), Soc. Mat. Sci., Japan, eds. T. Fukuda et aI.,
Elsevier Applied Science, pp. 81-96.
T. Uenoya (1994b), Symp. Interfacial Mal. Sci. on Composites, III, presented in a poster session, Osaka.
W.L. Wu (1990), SAMPE. J., 26, 11-15.

6102

INDEX to Journal of Acoustic Emission, Volume 13
Contents
Numbers 1/2

Pages 1-10

Early Detection of Damages in Journal Bearings by Acoustic Emission Monitoring Dong-Jin Yoon,
Oh-Yang Kwon, Min-Hwa Chung and Kyung-Woong Kim
Clustering Methodology for the Evaluation of Acoustic Emission from Composites
Pages Jl-22
A. Ao Anastassopoulos and T. P. Philippidis
Investigation of AE Signals Emitted from an SiOx Layer Deposited on a PET Film
Pages 23-29
Masa-aki Yanaka, Noritaka Nakaso, Yusuke Tsukahara and Nelson N. Hsu
On Characterization and Location of Acoustic Emission Sources in Real Size Composite Structures Pages 31-41
A Waveform Study M. A. Hamstad and K. S. Downs
Conferences and Symposia: 12th International Acoustic Emission Symposium
A Waveform Investigation of the Acoustic Emission Generated during the Deformation and Cracking ofPages SO1-07
7075 Aluminum Steve H. Carpenter and Michael R. Gorman
Acoustic Emission and Damage Evolution in an SiC Fiber Reinforced Ti Alloy Composite
Pages S08-13
K. Takashima, H. Tonda and P. Bowen
Cracking Process Evaluation in Reinforced Concrete by Moment Tensor Analysis of Acoustic Emission
Pages SI4-20
Shigenori Yuyama. Takahisa Okamoto, Mitsuhiro Shigeishi and Masayasu Ohtsu
The Interaction between Pore Auid Pressure Changes and Crack Damage Evolution in Rocks andPages S21-28
Subsurface Rock Structures Modeled from Acoustic Emission Data Peter Sammonds. Philip Meredith.
Javier Gomez and Ian Main
Acoustic Emission Analysis of TiAIlntennetallics Manabu Enoki and Teruo Kishi
Pages S29·34
Recent Applications of Acoustic Emission Testing for Plant Equipment
Masashi Amaya
Pages S35-41
Effects of Soil Acidity on Acoustic Emission Properties of Sugi (Cryptomeria Japonica) SeedlingPages 542-46
Keiichi Sato, Atsushi Uchiyama, Takeshi Izuta. Makoto Miwa, Naoaki Watanabe, Takafumi Kubo andMasami Fushitani
Acoustic Emission of Bending Fatigue Process of Spur Gear Teeth
Pages S47-53
Kouitsu Miyachika, Satoshi Oda and Takao Koide
Characterization of Thermal Cracking by Acoustic Emission Time Series Analysis
Pages S54-59
Koji Nagano, Katsuhiro Sugawara, Ken-lchi Itakura arxI Kazuhiko Sato
Page 30
Pages 42-44
Page S60
Page S07

Future Meetings on Acoustic Emission
Historic Files (AEWG Meetings, AEWG Awards), T.F. Drouillard / Call for papers
Available Books on Acoustic Emission
Cover Photograph

Numbers 3/4
Composites
Pages 45-55

Correlation of Acoustic Emission Felicity Ratios and Hold-Based Rate Moments with Burst
Strengths of Spherical GraphiteJEpoxy Pressure Vessels. Karyn S. Downs and Marvin A. Hamstad
Correlation of Regions of Acoustic Emission Activity with Burst Locations for SphericalPages 56-66
GraphiteJEpoxy Pressure Vessels. Karyn S. Downs and Marvin A. Hamstad
A Study of Acoustic Emission-Rate Behavior in Glass Fiber-Reinforced Plastics,
Pages 67-77
AJ. Brunner, R. Nordstrom and Po Fliieler
The Deterioration of Foamglas@ under Compression Studied with the Acoustic Emission Technique,Pages 79-86
M. Wevers. D. Tsamtsakis, P. De Meester, E. Uria and H. Strauven
Localization of Acoustic Emission in the Fracture of Fiber Composites, Vladimir Krivobodrov
Pages 87-96
Investigation of Damage Development in Paper Using Acoustic Emission Monotoring,
Pages 97-100.
Per A Gradin and Staffan Nystrom
Conferences and Symposia: 11th International AE Symposium, Sapporo, Japan
Pages S61-S67 Acoustic Emission Behavior during Plastic Deformation of 8090 AI-Li Alloy,
Ki-Jung Hong, Hee-Don Jeong and Chong 500 Lee
Pages 568-S74 Development OfThermal Shock and Fatigue Tests of Ceramic Coatings for Gas Turbine Blades by AE
Technique, CoY. Jian, Tatsuya Shimizu, Toshiyuki Hashida, Hideaki Takahashi and Masahiro SaitoPages S75-S82

Fractals on Acoustic Emission during Hydraulic Fracturing
Ken-Ichi Itakura, Kazuhiko Sato, Koji Nagano and Yasufumi Kusano
Pages S83-S88 Acoustic Emission during Tensile Loading of Low Velocity Impact-Damaged CFRP Laminates,
Oh-Yang Kwon, Joon-Hyun Lee and Dong-lin Yoon
Pages S89-S94 AE Characterization of Compressive Residual Strength of Impact-Damaged CFRP Laminates,
Isamu Ohsawa, Isao Kimpara, Kazuro Kageyama, Toshio Suzuki and Akihiko Yamashita
Pages S95-S 102 Acoustic Emission Analysis on Interfacial Fracture of Laminated Fabric Polymer Matrix Composites,
Toshiyuki Uenoya
Page 78
Page 100
Page S74
Pages I-i

Future Meetings on Acoustic Emission
Cover Photograph and AECM-5
Professor Hideaki Takahashi (1940-1995)
Index to Journal of Acoustic Emission, Volume 13

Author Index
Masashi Amaya,
S35
A. A. Anastassopoulos,
II
S08
P. Bowen,
Steve H. Carpenter,
SOl
I
Min-Hwa Chung,79
P. De Meester,
31,45,56
Karyn S. Downs,
42
T.F. Drouillard,
Manabu Enoki,
S29
Masami Fushitani,
S42
Javier Gomez,
S21
SOl
Michael R. Gorman,
Per A Gradin,
97
31,45,56
Marvin A. Hamstad,Toshiyuki Hashida,
568
Ki-Iung Hong,56l
Nelson N. Hsu,
23
Ken-Ichi ltakura,
S54,575
Takeshi Izuta,
542
Hee-Don Jeong,
561
C.Y. Jian,
568
Kazuro Kageyama,
589
I
Kyung-Woong Kim,

1996 SUBSCRIPTION RATE

Isao Kimpara,
Teruo Kishi,
Takao Koide,
Vladimir Krivobodrov,
Takafumi Kubo,
Yasufumi Kusano,
Oh-Yang Kwon,
Chong 500 Lee,
Joon-Hyun Lee,
Ian Main,
Philip Meredith,
Makoto Miwa,
Kouitsu Miyachika,
Koji Nagano,
Noritaka Nakaso,
5taffan Nystrom,
5atoshi Oda,
Isamu Ohsawa,
Masayasu Ohtsu,
Takahisa Okamoto,T. P. Philippidis,
Masahiro 5aito,Peter 5ammonds,

S89
529
547
87
542
575

1,583
561
583
521
521
542
547
554,575

23
97
S47

S89
S14
S14

11

Kazuhiko 5~to,
Keiichi Sato,
Mitsuhiro 5higeishi,
Tatsuya 5himizu,
H. Strauven,
Katsuhiro Sugawara,
Toshio Suzuki,
Hideaki Takahashi,
K. Takashima,
H. Tonda,
D. Tsamtsakis,
Yusuke Tsukahara,
Atsushi Uchiyama,
Toshiyuki Uenoya,
E. Uria,
Naoaki Watanabe,
M. Wevers,
Akihiko Yamashita,
Dong-Jin Yoon,
Masa-aki Yanaka,
5higenori Yuyama,554,575
S42
514
568
79
S54
589
568

508
508
79
23
542
595
79
542

79
589

583
23
Sl4

S68
52l

for Volume 14$96 per volume for Vols. 9-13. US surface postages $8 pervolume. For Canada and overseas surface delivery. add $11 andfor air mail. add $30 per volume (will be adjusted for multivolume order).

Base rate for one year (four issues. Mar. - Dec.) $ 96.00
Add Postage of
U.S. - Book rate
$ 8.00All others - Book rate
$ 11.00
Western Europe/S. America - Air mail rate
$ 25.00
All others - Air mail rate
$ 30.00
Add$5 without payment upon order. Payment must be in U.S.
dollars drawn on a U.S. bank. Bank transfer accepted. but with
$10 surcharge to the A.E. Group account (Account No. 08003416470) at
Sumitomo Bank of California
San Fernando Valley Office15250 Ventura Blvd, Sherman Oaks. CA 91403-3262
Notify us of such a transfer as the bank cannot sometimes gi ve
us the name of the payer. One volume of four issues per year.
Index included in the Oct.-Dec. issue. Back issues available at$50 per volume for Vols. 1-3, $90 per volume for Vols. 4-8.

All orders should be sent to (or Fax 1-818-368-8309)
Acoustic Emission Group308 Westwood Blvd., Box 364
Los Angeles, CA 90024-1647 USA
For inquiry through Internet, use the following address:
ono@seas.ucla.edu
Editor-Publisher
Kanji Ono Tel. (310) 825-5233
Cover Design
Robin Weisz (UCLA Publications)
Production
Pace Publication Ans
Publication Date of This Issue: 20 February 1996.
I-ii

Notes for Contributors
l. General

The Journal will publish contributions from all parts of theworld and manuscripts for publication should be submitted
to the Editor. Send to:Professor Kanji Ono. Editor - JAE
6531 Boelter Hall. MSE Dept.
Univers ity of California
Los Angeles. California 90095-1595 USA
FAX (I) 818-368-8309
e-mail: ono@seas.ucla.edu
Authors of any AE related publications are encouraged tosend a copy for inclusion in the AE Literature section to:
Mr. T.F. Drouillard. Associate Editor - JAE
11791 Spruce Canyon Circle
Golden. Colorado 80403 USA
All the manuscripts will be reviewed upon submission to
the Editor. Only papers not previously published will be
accepted. Authors must agree to transfer the copyright to
the Journal and not to publish elsewhere. the same paper
submitted to and accepted by the Journal.

References to published literature should be quoted in the
text citing authors and the year of publication. These are to
be grouped together at the end of the paper in alphabeticaland chronological order. Journal references should bearranged as below. Titles for journal or book articles arehelpful for readers. but may be omitted.
H.L. Dunegan. D.O. Harris and C.A. Tatro (1968). Eng.
Fract. Mech.• I. 105-122.
Y. Krampfner. A. Kawamoto. K. Ono and A.T. Green(1975). "Acoustic Emission Characteristics of Cu Alloys
under Low-Cycle Fatigue Conditions," NASA CR-134766,
University of California. Los Angeles and Acoustic Emission Tech. Corp.• Sacramento. April.
A.E. Lord. Jr. (1975). Physical Acoustics: Principles andMethods. vol. 11. eds. W. P. Mason and R. N. Thurston.
Academic Press, New York. pp. 289-353.
Abbreviations of journal titles should follow those used in
the ASM Metals Abstracts. In every case. authors' initials.
appropriate volume and page numbers should be included.
The title of the cited journal reference is optional.

A paper is acceptable if it is a revision of a governmental ororganizational report. or if it is based on a paper publishedwith limited distribution.

Illustrations and tables should be planned to fit a single
column width (87 mm or 3.3") or a double width (178 mm
or 7"). For the reviewing processes. these need not be ofhigh quality. but submit glossy prints or equivalent with thefinal manuscript. Lines and letters should be legible.

An abstract of about 200 words is needed for Research andApplications articles. while it should be shorter than 100
words for other articles.

4. Review

The language of the Journal is English. All papers should
be written concisely and clearly.

2. Page'Charges
No page charge is levied. Fifty copies of off-prints will be
supplied to the authors free of charge.
3. Manuscript for Review
Manuscripts for review need only to be typed legibly;
preferably. double-spaced on only one side of the page withwide margins and submitted in duplicate.
The title should be brief. Except for short communications.
descriptive heading should be used to divide the paper into
its component parts. Use the International System of Units(SI).

All manuscripts will be judged by qualified reviewer(s).
Each paper is reviewed by one of the editors and may besent for review by members of the Editorial Board. The
Board member may seek another independent review. In
case of disputes. the author may request other reviewers.

5. Electronic MediaIn order to minimize typographical error. the authors arc
encouraged to submit a floppy disk copy of the text. We
can read Macintosh and IBM PC formats. Those who canconnect to INTERNET can send the text portion to"ono@seas.ucla.edu". This will greatly shorten the time ofcommunication.
6. Color PhotographWe can print color photographs needed to enhance thetechnical content of an article. Because of the cost. theauthor is asked to pay $350 per page.

Contents
Composites
Pages 45-55

Pages 56-66

Pages 67-77
Pages 79-86

Pages 87-96
Pages 97-100

Correlation of Acoustic Emission Felicity Ratios and Hold-Based Rate Momentswith Burst Strengths of Spherical Graphite'Epoxy Pressure Vessels,
Karyn S. Downs and Marvin A. Hamstad
Correlation of Regions of Acoustic Emission Activity with Burst Locations forSpherical Graphite'Epoxy Pressure Vessels,
Karyn S. Downs and Marvin A. Hamstad
A Study of Acoustic Emission-Rale Behavior in Glass Fiber-Reinforced Plastics.
A.J. Brunner, R. Nordstrom and P. FlUeler
1bc Dctcrioralion of Foamglas@ under Compression Studied with the Acoustic
Emission Technique. M. Wevers, D. Tsamtsakis, P. De Meester, E. Uria andH. Strauven
Locali7.ation of Acoustic Emission in the Fracture of Fiber Composites.
Vladimir Krivobodrov
Investigation of Damagc Devclopmcnt in Papcr Using Acoustic Emission
Monotoring, Pcr A Oradin and Slaffan Nystrom

Conferences and Symposia
Pages S61-S67
Pnges S68-S74

Pages S75-S82
Pnges S83-S88
Pages 589-S94

Pages S95-S102

Page 78
Page 100
Page $74
Pages I-i

12'· International AE Symposium, Sapporo, Japan
Acoustic Emission Behavior during Plastic Deformation of 8090 Al-Li Alloy,
Ki-Jung Hong, Hec-Don Jeong and Chong Sao Lee
Development OfThcmlal Shock and Fatigue Tests of Ceramic Coatings for Gas
Turbine Blades by AE Technique,
C.Y. Jinn, Tatsuya Shimizu, Toshiyuki
Hnshidn, Hideaki Takahashi and Masnhiro Saito
Fmctals on Acoustic Emission during Hydraulic Fracturing
Kcn-Ichi Itakura, Kazuhiko Sato, Koji Nagano and Yasufumi Kusano
Acoustic Emission during Tensile Loading of Low Velocity Impact-Damaged
CFRP Laminates, Oh-Yang Kwon, Joon-Hyun Lee and Dong-Jin Yoon
AE CharaCleriz.a1ion of Compressive Residual Strength of Impact-Damaged CFRP
Laminates, Isamu Ohsawa, Isao Kimpara, Kazuro Kagcyama. Toshio Suzuki
and Akihiko Yamashita
Acoustic Emission Analysis on Interfacial Fracture of Laminated Fabric Polymer
Matrix Composites, Toshiyuki Uenoya

Future Mcctings on Acoustic Emission
Cover Photograph and AECM-5
Professor Hideaki Takahashi (194Q.1995)
Index to Journal of Acoustic Emission, Volume 13