MECHANICAL TECHNOLOGY INC.

(NASA-CE- 178739) lUBBCMACfUNE E Y INCIPIENT

FAILUBE DYNAMI C C£IECTIC N JNEICATOfi S AN D

ANALYSIS final Ret-crt, Hay 1982 - Nov. 1983

(Shaker Research Corp.) 5<+ p HC A04/MF A^^

. CSCL 131 G3/37

N86-2 1857

Unclas

05843
MTI 85TR60

TURBOMACHINERY INCIPIENT FAILURE

DETECTION INDICATORS AND ANALYSIS

Prepared for:

National Aeronautice

& Space Administration

George C. Marshall

Space Flight Center

August 1985

SHAKER RESEARCH CORPORATION

968 Albany Shaker Road

Latham, New York 12110
MTI 85TR60

TURBOMACHINERY INCIPIENT FAILURE

DETECTION INDICATORS AND ANALYSIS

Prepared for:

National Aeronautics & Space Administration

George C. Marshall Space Flight Center

August 1985

SHAKER RESEARCH CORPORATION

968 Albany-Shaker Road

Latham, New York 12110
Unclassified

SECURITY CLASSIFICATION OF THIS PAGE (When Data Entered)

REPORT DOCUMENTATION PAGE

READ INSTRUCTIONS

BEFORE COMPLETING FORM

I. REPORT NUMBER 2. GOVT ACCESSION NO. 3. RECIPIENT'S CATALOG NUMBER

4. TITLE (and Subtttle)

TURBOMACHINERY INCIPIENT FAILURE DYNAMIC

DETECTION INDICATORS AND ANALYSIS

5. TYPE OF REPORT i PERIOD COVERED

Final (5/82 - 11/83)

S. PERFORMING ORG. REPORT NUMBER

MTI 85TR17

7. AUTHOR(»

D.R. Faby

R.L. Smith

J.L. Frarey

3. CONTRACT OR GRANT NUMBERC»>

NAS8-34683

9- PERFORMING ORGANIZATION NAME AND ADDRESS

Shaker Research Corporation

968 Albany-Shaker Road

Latham, New York 12110

10. PROGRAM ELEMENT. PROJECT, TASK

AREA 4 WORK UNIT NUMBERS

1 1. CONTROLLING OFFICE NAME AND ADDRESS

National Aeronautics and Space Administration

George C. Marshall Space Flight Center

Marshall Space Flight Center, AL 35812

12. REPORT OATS

8/12/85

13. NUMBER OF PAGES

46

14. MONITORING AGENCY NAME 4 AOORESSC// diifarmt Irom Controlling OHiee) IS. SECURITY CLASS, (at Otis report)

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1S«. OECLASSIF1CAT1ON/DOWNGRADING

SCHEDULE

IS. DISTRIBUTION STATEMENT (al tnie Report)

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17. DISTRIBUTION STATEMENT (ol the abstract an farad In Stock 20, II different trom Report)

18. SUPPLEMENTARY NOTES

9. KEY WORDS (Continue) on reverse tide it naceaaary and identity by block matter)

Incipient Failure Detection (IFD)

Turbomachinery

Vibration Analysis

Turbo Pump

0. ABSTRACT (Continue on reverse it da it necaaeary and identify lay block nuatoar)

Tape recorded signals from case-mounted accelerometers are examined to determine

the feasibility of detecting spalls on bearing balls in the liquid oxygen (LOX)

pump in the Space Shuttle Main Engine (SSME). The nonperiodic nature of the spall

impact on inner and outer bearing races caused traditional techniques to be unsuccessful. A technique involving statistical techniques and spectra ratios was

used to review available pump test tapes.

00 ,

FORM

JAN 73 1473 EDITION OF I MOV 65 IS OBSOLETE

Unclassified

SECURITY CLASSIFICATION OF THIS P A.GE (Whan Data Entarad)
TABLE OF CONTENTS

SECTION PAGE

LIST OF FIGURES

1.0 INTRODUCTION 1

2.0 BACKGROUND 3

3.0 DISCUSSION OF RESULTS 6

3.1 Rolling Element Bearing Failures 6

3.2 Review of Supplied Data Tapes 9

3.3 Computer Analysis of Supplied Data Tapes 12

3.3.1 Computer Programs for Reviewing Data 12

3.3.1.1 Loading Tape Data to Computer 12

3.3.1.2 Data Manipulation and Analysis 15

3.3.2 Computer Review of Tape Data 16

3.3.2.1 Spectral Maps 16

3.3.2.2 Sum Averaging 16

3.3.2.3 Dispersions of Spectra 16

3.3.3 Comparison of Signals 20

3.3.3.1 Diagnostic Comparison 20

4.0 DISCUSSION OF RESULTS 25

5.0 RECOMMENDATIONS 26

Appendix A 27

Appendix B 46
LIST OF FIGURES

Figure 1 - Location of Accelerometers Sensing

Turbine Bearing

Figure 2 - HP 5451C Data Processing System at Shaker Research

Figure 3 - Failure Detection Signals from Typical Rolling

Element Bearings

Figure 4 - Relative Spectrum Sum Average from Three Completed

Passes over Tape

Figure 5 - Peak Amplitude Response with Time

Figure 6 - Spectra Peak Amplitudes versus Time for Four

Bearing Frequencies

Figure 7 - Computer Programs Menu

Figure 8 - Schematic of Spectra Review Technique

Figure 9 - Ratio of Two Dispersion Spectra

Figure 10 - Ratio Enhancement of "Cage Only Defect Signals" using

Dispersion Sepctra

Figure 11 - Frequency Distribution (Histogram)

Figure 12 - Rank Ordered Ball Spin Frequency Amplitudes and

Histograms

PAGE

7

8

10

11

13

14

17

18

19

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23

Figure A-l- Computer Programs Menu 30
1.0 INTRODUCTION

The purpose of the work described in this report was to review several NASA

supplied data tapes using a previously developed Incipient Failure Detection

(IFD) technique. The developed (IFD) technique was described thoroughly in a

previous Shaker report (1), but a brief description is included herein for

completeness. The (IFD) procedure was intended for use on the space shuttle

liquid oxygen (LOX) turbine-pump bearings, and for general use on high-speed

turbomachinery. The tape recorded data used during the study was originally

taken from a series of LOX pump tests performed on a rocket engine by NASA-MSFC

engineers. The tape library used in the present study consisted of fourteen

tapes each with 300 seconds of recorded information. Each tape had fourteen

channels of information taken from a variety of test sensors.

Machinery component degradation and ultimate failures have been explored in the

past for a characterization of the failure onset mechanisms and their detection.

Analysis schemes which have provided meaningful failure prevention signals on

some occasions may not have proven effective on another. Success of an Incipient Failure Detection (IFD) technique in a given application can depend upon

many factors. The technique itself may be viable but the environment to which

it is applied may not be suited to the selected scheme of detection. In addition, a known environment may not lend itself simply to any previously applied

detection schemes, and new concepts may have to be applied in order to provide

adequate system protection.

A potential method for extracting asynchronous vibratory failure information

was identified by Shaker Research in a previous contract with NASA. Traditional

methods of signal extraction had not been effective since most of these schemes

rely upon the long term presence of repetitive signals. The character of the

intermittent ball defect signal was more like noise than it was like a stationary failure signal, and consequently was averaged out of the data by tradition

approaches. A statistical technique was developed during the previous project

that made use of the ratio of two typical methods of data analysis. The identified method of ratioing showed promise of being able to detect incipient degradation of rolling element bearing components.
This report presents the efforts involved in surveying a set of available (LOX)

pump tape data with the new failure detection concept. Results are presented

for sensor locations near the failed bearing, as well as, on the outer housing

of the turbine-pump structure.
2.0 BACKGROUND

Because of Che reusability concept of the space shuttle program, monitoring and

diagnosis of impending mechanical failure are important aspects to NASA. The

project reported herein investigated diagnostic techniques that would allow the

identification of impending failure of the space shuttle main engine (SSME)

liquid oxygen (LOX) pump turbine-end bearing.

.Available data in a previous Shaker contract included vibration, acceleration,

pressures and temperatures measured and recorded during rocket engine tests.

Three data recordings of the Challenger's SSME test series were made available

to SRC. The first tape, ID #901-339, was recorded early in the test series and

was thought to contain data representative of "good" bearing operation. Tape ID

#901-340 was recorded mid series and was thought to contain data of "broken in"

components, while the last tape of the series, ID #901-352, was thought to have

been recorded with a spalled ball in the turbine-end bearing.

The recorded data included accelerometers which were mounted on the outer casing

flange of the pump as depicted in Figure 1. Ideally, sensors should be located

as close to the bearing as possible. In this case, however, the structural path

between bearing and sensor was indirect and distant. The content of the

recorded acceleration data was all low-frequency, less than 10 KHz. Traditionally, successful rolling element bearing analysis techniques have been made

on data at 20 KHz and above. In addition the data contained high level pump and

turbine blade pass frequencies which dominated the frequency spectrum and fell

within the frequency range of the calculated rolling element defect frequencies.

This provided a very low signal-to-noise ratio for the bearing related frequencies of interest. Because of these problems, it was questionable whether or not

the tapes contained defect information and, if so, how was it to be unmasked

from normal operating signals present.

Traditional vibration analysis techniques were ineffective due to the nonperiodic nature of the defect signal (spalled balls). These techniques could not

sufficiently enhance the defect amplitudes in the presence of such signals as

the blade passing signal.
ORIGINAL PAGE IS

OF POOR QUALfTY

i 4
Section 3.0 of this report discusses in detail the application of a ratioing

technique which showed some enhancement of the defect frequencies under such

conditions. The technique used is statistically based and may have promise of

application to high-speed turbomachinery in general.
3.0 DISCUSSION OF RESULTS

NASA provided several data Capes that were reviewed during the present study.

Each tape contained approximately 300 seconds of data on each of fourteen channels provided for storage. Recorded signals were derived from internally mounted sensors, as well as, outer case mounted devices. Both strain gage and

accelerometer type devices were used in generating the recorded vibrational

information. Several reviews of the available data were made in order to establish the detectability of (or lack of) incipient failure signals. Signals were

reviewed with the standard Nicolet spectrum analyzer, as well as, with the HP

5451C Fourier Analyzer System (shown in Figure 2). The details of the data tape

review and the procedures developed for the detection of rolling element bearing

component failure are contained in this section of the report.

3.1 Rolling Element Bearing Failures

Bearing failure detection can be represented schematically as a function of time

by a plot similar to those shown in Figure 3. Although no single failure might

follow the curve(s) shown it is known that bearings generally follow the trends

displayed by the plot. Region one of Figure 3, portrays the tendency for new

bearings to become "quieter" after a short period of break-in. This is normally

attributed to the irregularities of construction being smoothed-out after a

short period of running.

The second region of failure signal detection is schematically represented by

the middle portion of the diagram. This represents the typical quiet period for

the majority of a normal bearing's operating life. In practice this diagnositic

signal is well below the typical failure warning level provided by conventional

failure detection devices.

The third time block depicted in Figure 3, is the period of incipient failure

found in most rolling element bearings. During this period the typical diagnostic signal increases steadily in strength until the bearing fails catastrophically. However, signals similar to that depicted by the dotted trace are

occassionally observed. For example, the dotted trace shown could represent the

effects of small chunks of metal being released from within the bearing.
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The signals could quickly subside however, as the particles become worn or

spread throughout the bearing (or thrown off to the side of it).

The goal of any successful incipient failure detection method is to determine

the instant at which the bearing system has entered the third (see Figure 3) or

final stage of its operating life. The sooner it is known that a bearing has

entered its final stages of operability the sooner action can be taken to

prevent catastrophic failure. Incipient failure signals might also be used for

initiating system maintenance actions. Advance notice and change-out of critical component substructures could then insure future safe operation.

3.2 Review of Supplied Data Tapes

Appendix B contains a list of the data tapes supplied to Shaker for review with

the developed analytical techniques. Both the conventional real time spectrum

analyzer and the computerized HP 5451C Fourier analyzer were used in reviewing

the tapes. The tapes reviewed contained signals which were mounted inside, as

well as, outside the pump and turbine test fixture.

A typical analog spectra of the test data is shown in Figure 4. This is a multipass average of the available spectral information and contains an image of the

engergy available in the 0-5000Hz band. A limited amount of information is

available above the band shown.

Traditional failure analysis techniques would anticipate increases in the

displayed spectrum amplitudes at the identified bearing component frequencies

as these components began to fail. Normal bearing operation will usually result

in slight variations of the spectral peaks even in steady-state operation. This

time variation of peaks is depicted schematically in Figure 5, for a spectral

peak which is shown passing from normal operation into abnormal operation. The

selected spectral peak distribution has gone from a relatively low average to a

higher value. This is indicative of the increased energy present at the

frequency shown.
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To be sure that signals of bearing components which were undergoing periods of

stress could be observed in this manner one of the supplied tapes were reviewed

from beginning to end for specific amplitude changes. The results displayed in

Figure 6, represent the full amplitude changes of four specific bearing related

frequencies over the extent of the test tape. From this review it was established when the cage failure occurred on the tape. In addition, it can be seen

that high amplitude spikes at the ball and outer race defect frequencies did

occur prior to the ultimate cage related failure. Point "c" in the ball defect

signal is the first indicator of an abnormal signal amplitude. This signal is

roughly two times the height of the nominal distribution established by the

bearing sensor up to that point in time.

The total time span shown is approximately 250 seconds or 125,000 revolutions of

the test bearing. The 4x running signal amplitude shown was reduced by a factor

of four for presentation purposes.

3.3 Computer Analysis of Supplied Data Tapes

3.3.1 Computer Programs for Reviewing Data

Appendix A contains a set of program listings for the type of analysis used in

the present study. The programs listed operate from a main selection menu shown

in Figure 7. Spectral analysis resulting in plotted outputs representing sums,

differences, dispersions (variances), peak hold, ratios, and histograms can be

performed with the programs included. In addition, combinations of these

routines can be accomplished by saving intermediate computations onto disks for

later recall and manipulation.

3.3.1.1 Loading Tape Data to Computer.

The 5451C Fourier Analyzer System can perform analysis of time and frequency

data containing frequencies from D.C. to 50KHz. The system can be used to

analyze time-series data from mechanical vibrations and acoustic phenomena.

These analyses can be used to detect hidden signals in noise, or locate critical

functions in complex systems. Programmed steps can be used to perform a partic12
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ular set of operations. Programs, as well as, analyzed data can be stored on

hard disks for re-entry and review with the Fourier Analyzer.

Data input and loading is controlled from keyboard programs such as the ones

listed in Appendix A (Stacks "5" and Stacks "12" & "18"). Data is entered

through the Analog-to-Digital Converter in digital form onto the hard storage

disk 7900. Results of all data operation are displayed on the oscilloscope

contained in the 5451C system. Results can be printed or plotted on the CRT or

hardcopy printer.

Externally triggered sampling of data is often required to get the sprectral

information on an "order" basis. This procedure may be required when the-taped

data is from a system which is varying in speed during the recorded period of

interest.

3.3.1.2 Data Manipulation and Analysis Procedures.

All the programs listed in Appendix A operate in general as follows:

1. Load from Stack "0" the Menu program

2. Use the 5451C keyboard to jump to Label "0". (Wait for plot to be

completed and the full menu to appear)

3. Select desired Menu control by entering the number of the menu item to

be run

4. Either enter second requested entry when questions appears, or wait for

plot to appear on CRT (if no second entry is required)

5. After reviewing plot enter any numeric key for return to main menu

6. If desired make intermediate copies on printer from CRT.

15
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3.3.2 Computer Review of Tape Data

Several sets time based data were Loaded to the computer disk storage files. In

the final analysis of the tape data this provided for the manipulation and

review of individual, as well as, combinations of stored spectra. Spectra

stored in the computer are usually loaded in a contiguous fashion on the basis

of time from the original data tapes. See program for loading data from tape to

computer in Appendix A.

3.3.2.1 Spectral Maps (Waterfall Plots).

Plots similar to those displayed in Figure 8, are spectra maps of contiguous

time blocks taken from recorded tape data. A single peak frequency element of

these contiguous blocks of data can be charted over the time represented by

stored data. The side view of the spectral map displays how the amplitude of a

single frequency band will vary over time. It can be seen in Figure 8, that a

single peak amplitude varies to some extent as the recording proceeds. The

extent to which a peak varies with time is partially dependent on the condition

of the bearing system which generates the signals, as will be shown in a later

section.

3.3.2.2 Sum Averaging.

Ensemble sum averaging as displayed previously (Figure 4), was used to establish

the mean values of the spectral peaks. These sums were used in two ways; 1) for

establishing the expected amplitudes present in the system spectral energy

output and 2) for relative normalization of subsequent spectra by ratioing.

3.3.2.3 Dispersions (Variance) of Spectral Amplitudes with Time and Ratio.

One character of the distribution created by spectral peak amplitudes is the

dispersion (or variance). The dispersion is a measure of the distribution

width; where the width in this case is a measure of how much a given peak varies

in time.

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The dispersion of bearing component frequencies is apparently dependent upon

their amplitudes. This is graphically shown in Figure 9. Shown are two (the

smaller spectra on the left) dispersion spectra (peak variance at every frequency) when there was a bearing defect present (upper) and when there was no defect

present (lower).

Ratioing these two spectra provides an increase in amplitude or enhancement of

the bearing component frequencies which were operating under conditions of near

failure. The reason for the presence of a few other peaks (non-component

frequencies) in the ratio plot was not established. However, the two peaks near

the 500 cycle running frequency comes about because of their very low amplitude

components (almost zero) in the dispersion plot without defect present. The 4x

times running spike may be extra large because of variations in vane passing

energy under the two separate conditions of running.

Ratioing spectra from two other portions of the data also shows that the "cage

only" defect signal can be enhanced to be greater than the dominate 4x times

blade passing signal. This is shown in Figure 10.

3.3.3 Comparisons of Signals from Four Separate Data Tapes

Discussion to this point has centered on the development of diagnostic methods

which can provide failure onset detection. The methods of ratioing two average

spectra; one which has definite failure content to one which is representative

of the systems long term non-defective nature has been shown to be effective.

Up to this point the major discussion has centered around signals which are

gathered from internal rig mounted sensors. The discussion which follows

compares data not taken from internally mounted sensors; but from external

sensors. Signals from these sensors have had to travel from the source (bearing) through several mechanical interfaces and typically have a different power

distribution than the internally mounted sensors.

3.3.3.1 Approach to Diagnostic Comparison of Tapes.

Previous work (see Reference 1) established that enhancement of bearing compo20
nent frequency peaks could be attained through ratioing. The impetus for these

methods was derived from the fact that component frequency spikes could occasionally be enhanced when a moving average of 4-8 spectra (window average) was

compared (ratioed) to the sum average of the whole tape.

When a failure onset signal on internally mounted sensors is present from a

rolling element bearing two changes in component frequency peak amplitude occur.

First the component frequency amplitude increases, and secondly there may be a

broadening of the frequency distribution at the new (higher) amplitude. Both of

these characteristics are depicted schematically in Figure 11.

Shown also in Figure 11, is a residual low-amplitude portion of the distribution

which portrays the possibility of a mixed operating character of the bearing.

When a bearing is operating during the onset of a failure mode it is possible for

the high amplitudes to be pulsed in nature. The sporadic nature of this type of

operation would provide some low amplitude signals, as well as, high amplitudes

and was displayed from the data tapes in Figure 8, shown in a previous section.

In view of this preliminary conclusion involving failure component signals four

different tapes were reviewed:

1. No-Known Defects (TAPE 211 #1)

2. Cage Onset Defect (TAPE 212 #1)

3. Possible Spall Defect (TAPE 352 #3)

4. No-Known Defects (TAPE 339 #1)

The externally mounted 90° radial accelerometer on the high pressure turbine end

of the test rig was used in the following review. It was known that diagnostic

success could be attained from internally mounted sensors and it was conjectured

that externally mounted sensors might prove amenable to a similar analysis.

Some resulting plots taken from the four tapes reviewed are displayed in

Figure 12.

21
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Typical Non-Defect Signal

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FIGURE 11 - Frequency Distribution (Histogram)

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It is not clear that the frequency distributions taken from 128 spectra from

each tape reveal the appropriate diagnostic results. Although the tape contining the "cage onset" defect signals does display a skewed distribution (counts

on the right side of the histogram shown), so does the last tape reviewed which

does not have any known defects present during the recording. In other words,

the results from a distributive view appear inconclusvie when signals from

externally mounted sensors are considered.

24
4.0 DISCUSSION OF RESULTS

This project involved scanning several. NASA-provided data tapes each containing

approximately 6 internally mounted , as well as, externally case-mounted accelerometer signals from LOX pump testing. The analysis performed made use of the

conventional spectra analyzer, as well as, the HP 5451C. Programs for storing

and analyzing data on the HP 5451C Fourier Analyzer were transferred to NASA.

Although the developed procedures for enhancement of bearing failure signals

could be demonstrated on signals obtained from internally mounted strain gages,

the results were less encouraging when externally mounted accelerometers were

the source for sensing vibrations.

Taped data from internally mounted sensors appeared amenable to programmable

analysis which enhanced the defect signal relative to the noise present in the

signal. Techniques which involved ratioing two sets of spectral information

provided the following conclusions:

1. Non-repetitive pulses from defective bearing components can be

enhanced by comparing the pulsed portions of the taped signal to the

sum average of the signals time history

2. Spectral peaks corresponding to bearing components defect tend to:

a. Increase in amplitude as the defect becomes more pronounced, and

b. become more dispersive (have larger variances) in their resulting

distribution.

Taped data from externally mounted sensors when viewed with algorithms which

enhance failure on-set signals from internally mounted sensors did not yield

conclusive diagnostic results. Either the failure component signals were too

small to be detected or the captured spectra reviewed (typically 128 per tape)

were not from the appropriate sections of tape which corresponded to the component failure output signal.

25
5.0 RECOMMENDATIONS

1. The techniques used during the present study could be more fully examined if computer storage were available for processing a larger number

of spectra. It is possible that the analysis of the signals obtained

from the externally mounted sensors was not broad enough; a 128 spectra

was the maximum available per review attempt in the present HP 5451C

system. These signals may require 20 to 50 times the available spectra

in order to resolve the small amplitude pulsed signal which may be

present in the taped information.

2. Moving based spectral averaging windows compared to long term history

of the system average spectra when processed and scanned over the full

extent of the tape may improve the chances of capturing significant

"defect" signals.

3. All comparison of spectral signals should be done on an orders basis

(if possible) so that slight variations in speed do not "average out"

the small signal at a given frequency which might be present.

4. Use of High frequency (0-40,OOOHz) sensors and recording instrumentation may be used along with resonant demodulation technology in order

to discriminate the small energy pulses which eminent from the onset of

bearing defects.

5. Test runs could be made on the statistical distribution character of a

large number of spectra from a test rig which could be set up with

"known" bearing defects in order to review failure detection methods

under controlled conditions.

26
APPENDIX A

PROGRAM MENU SELECTIONS

and

PROGRAM LISTINGS
Contained in Appendix A are Listings of the HP 5451C programs which are relevant

to the work described here. When the program of stack "0" is accessed the menu

selections of Figure A-l are available for operation. A wide variety of plotted

outputs ranging from the dispersions of a group of spectra to the rank ordered

display of a selected channel of all 128 stored spectra are provided. A

description of how each of the 12 selections can be used to process stored spectral information follows. (Refer to Figure A-l).

Menu Selection ( ) 1 - Stores data to disk from ADC in form of Spectra.

Previously taped data loaded through the analyzer with a program such as that

shown in the listings under stack "5" can be converted with the programs listed

under the stack "12" and "18" headings. This particular function is the only

part of the program included in the present work which will not operate automatically and must be accessed manually from the 5451C keyboard. This prevents the

accidential selection of this menu item which could result in an improper over

writing of the stored spectral data.

Menu Selection ("') 2 - Ranks Disk Spectra Amplitude from Channel you Select.

The amplitudes of a selected channel of all spectra are re-order into a ranked

file of the smallest to largest amplitude. The progress of the reordering process can be viewed on the oscilloscope of the 5451C. Total ranking time for this

selection is about 30 sec. to one minute. The spectrum with the biggest amb.

amplitude, second biggest, etc., can be located by checking the ranked file

number list of the stored spectra.

Menu Selection (*) 3 - Plot Spectrum from a Selected Disk File.

This routine allows one to review any of the available spectra though plotting

them on the CRT or printer.

Menu Selection (*) 4 - Plot Peaks of All Spectra from a Selected Channel.

A provision for obtaining a "side view" of the spectral map of all the spectra is

the basis of this calling routine. The location of the side view is provided for

27
in the channel number selection. There are 256 channels in the displayed spectra of these routines which represents the zero to full scale frequency of the

stored spectra.

Menu Selection (*) 5 - Graph Maximum Peak Heights of a Group of Spectra.

This portion of programming is similar to the "Peak Hold" operation of the standard commercial spectrum analyzer. The largest peak of all spectra in every

channel (frequency) of the selected group of spectra are sought-out and

displayed by the routine.

Menu Selection (''") 6 - Graph Minimum Peak Height of a Group of Spectra.

Similar to the previous menu selection.

Menu Selection (*) 7 - Plot the Difference Between Two Spectra.

Any two stored spectra may be recalled for this computation.

Menu Selection (*) 8 - Plot the Relative (%) Difference Between Two Spectra.

Any two stored spectra can be recalled and operated upon in this manner. The

values computed for each channel follow the form:

(A - B) *100

B

where A and B represent the numeric amplitudes of each channel of each spectra.

Menu Selection (*) 9 - Plot Ratios of Average of Two Groups of Spectra.

The computation called for by this selection involves three steps. First the

two stored groups of spectra are identified as two contiguous sets of stored

spectra through input selection. Then ensembled averages are computed automatically for the two identified sets. Finally, a ratio of these averages is

computed channel by channel (frequency-by-frequency) over the whole range of

frequencies.

28
Menu Selection (*) 10 - Plot Ensemble Sums Average of a Group of (N) Spectra.

The following form is used to compute:

N

X,) /N

i = 1 n

the sum average for each channel (frequency) is computed over the group of spectra selected.

Menu Selection (*) 11 - Plot Dispersion (Variance) of a Group of Spectra.

This computation invloves the evaluation of the formula:

N g.(A)2 - ( A)2

N (N - 1)

for each channel (frequency) over the group of spectra selected. Where A is the

amplitude of selected channel.

Menu Selection (*) 12 - Plot Histogram of all Spectra from a Selected Channel.

An amplitude distribution of a selected channel from all stored spectra can be

plotted.

29
C

MUOCD

LLJ crooccQ.

'ECTRA U-coLL02cr0u.ZQ0<20crLL*COQOH<<QCOLUCCoCO

oLULUCO^O>_1LUZZ<020a:LLAMPLITUDES

<i. <crLUCLCO*COQCO^Z<cc

LU_lLLXCOQQA SELECTE 2OccLLPECTRUM CO!-gQ.

CHANNEL QA SELECTEI 2OQCLL<QCOLUQ.CO_l_!<LLOCO*:<LU0.(-O_jCL

SPECTRA LLA GROUP 0 LLHEIGHTS 0 *<LUa.MAXIMUM X0_<cro

SPECTRA 1 1 ^ GROUP OF *<HEIGHTS OF be<LUCLMINIMUM XQ.<CCo

O SPECTRA §BETWEEN T LUOZLUHE DIFFER KH0CL

\/O SPECTRA >BETWEEN T LUDIFFERENC £LU>§LUOCLUXH1-oCL

<DC0LUQ.COLLGROUPS Ol O$LL0COLUO<CCLU><LLOCOO<cri-oQ.

SPECTRA , GROUP OF <VERAGE OF <2z>(r>NSEMBLE i LUh-oCL

ECTRA a.COLLOCL3Ocro<LL0OJu<c

|

rISPERSION QHoCL

CTED CHANNEI L_U!LUCO<2OCCLL<QC0LUCLCO_l1 <LLOISTOGRAM X(—oCL

T- f\J C*J

COco

O> O i- CN

J

oCOccaoca. Occ< 2 » j II 2 <

uOJ

'oi

oo3COJ CJS- o4-

cr> oQ. CUCLEOoI Q;

30
/////////// MENU SELECTION PROGRAM ////////////

i L

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18 L

22 BS

2.6 Y

30 Y

35 Y

40 Y R

45 Y #

52 J

56 L

60 J

64 L

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73 J

77 L

81 J

36 J

90 L

94 J

99 J

103 L

107 J

112 J

116 L

120 J

125 J

129 L

133 J

133 J

142 L

146 J

151 J

155 1...

1S9 J

164 J

163 L

172 J

177 J

181 L

185 J

1.90 J

194 L

198 J

203 J

207 L

211 J

21 S i...

219 J

223 .

0

5821

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ORIGINAL PAGE !S

OF POOR QUALITY

OD 10

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31
ORIGINAL PAGE IS

OF POOR QUALITY

c,

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32
ORIGINAL PAGE 53

OF POOR QUALITY

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33
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34
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35
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INSERT IF FILTERS REQUIRED

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19 MB

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GATHERS AND TRANSCRIBES DATA FROM TAPE RECORDER INPUT

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36
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37
////////////////////////////

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////////////////////////////

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REQUIRES STACK '20'

2 o o o :o

RSMKS DISK SPECTRA flMPLITUDES FROM CHANNEL YOU SELECT

38
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FROM A SELECTED CHANNEL (FREQUENCY).

39
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< SEE STACK '18' FOR STARTING 9 FILE '0' )

40
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41
/////////// MEMORY STACK '14' ////////////

NOT USED

/////////// MEMORY STACK '15' ////////////

NOT USED

/////////// MEMORY STACK '16' ////////////

NOT USED

42
MEMORY STACK '17'

o

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34 MS:''

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41

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3:1

SIMILAR TO STACK '12'

ALTERNATE FORM USING 'RECT' OPERATION

i

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NOT USED

OF .pr>~.«>

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45
APPENDIX B

LIST OF SUPPLIED DATA TAPES
LIST OF TAPES

//

1

2

3

4

5

6

7

8

9

10

11

12

13

14

Code

A3

A3

A3

A3

A3

A3

A3

A3

A3

A3

A3

A3

A3

A3

Number

212

211

231

212

215

214

215

212

215

214

232

227

214

225

Tape

1

1

1

4

1

4

4

5

5

1

1

1

5

1

Cals

15

15

15

15

15

15

15

15

15

15

15

15

15

15

Data

240

159

15

175

150

156

150

180

150

150

150

150

150

150

Dated

12/20/84

12/20/84

12/17/84

12/17/84

01/14/85

02/23/85

12/17/84

12/17/84

12/17/84

01/14/85

12/17/84

12/17/84

12/17/84

12/17/84

46
MECHANICAL TECHNOLOGY INC.

SHAKER RESEARCH CORPORATION 968 Albany-Shaker Road Latham, New York 12110 518/785-2211