Distributed sensing with OFDR and its application
to structural health monitoring
Hideaki Murayama1, Hirotaka Igawa2, Koji Omichi3 and Yuichi Machijima4
1

School of Engineering, The University of Tokyo, 7-3-1 Hongo, Bunkyo-ku, Tokyo, 113-8656 Japan
2
Japan Aerospace Exploration Agency, 6-13-1 Osawa, Mitaka, Tokyo, 181-0015 Japan3
Fujikura Ltd., 1440 Mutsuzaki, Sakura, Chiba, 285-8550 Japan
4
Lazoc Inc., 3-40-9 Hongo, Bunkyo-ku, Tokyo, 113-0033 Japan
ABSTRACT

Optical fiber sensors are promised candidates as sensor elements in structural health monitoring (SHM). Especiallyfiber-optic distributed strain sensors that return a strain value as a function of linear position along an optical fiber havebeen attractive for people in the field of SHM. We have developed a distributed strain sensing system using long-length
fiber Bragg gratings (FBGs), based on optical frequency domain reflectometry (OFDR). We employ long-length FBGs
whose length is about 100 mm and the sensing region, in other words the gauge length, can be expanded up to more than
1 m by serially-cascaded long-length FBGs. This sensing system has the high spatial resolution of less than 1 mm. In thispaper the distributed sensing system with OFDR and its application to SHM are described.
Keywords: distributed sensing, long-length FBG, optical frequency domain reflectometry, structural health monitoring

1. INTRODUCTION
In structural health monitoring (SHM) the sensor elements are required to monitor a measurand which can be affected bydamage or deterioration at positions interested. If the existence, location and type of damage in a structure are detected
and identified based on measured results, we can assess the structural integrity which indicates how much the structure
has strength margin. Then it can lead us to implement effective maintenance and safety operation. Effectiveness of theassessment of the structural integrity depends on the accuracy of the identification of damage. Frequently damage
reconstructs a stress distribution around it or changes the stiffness of a structural member. This means that we can noticethe existence of damage by detecting the fluctuation or the variation of the strain distribution. In some cases the locationand type of damage can be also identified by analyzing the strain distribution. In a complicated structural system, such as
aircraft, ship, or bridge, a lot of structural members are carrying loads as supporting each other to keep the whole
structure. Therefore the ability of comprehensive monitoring in the structure is useful for SHM.
Optical fiber sensors are promised candidates as sensor elements in SHM. Especially fiber-optic distributed strain
sensors that return a strain value as a function of linear position along an optical fiber have been attractive for people in
the field of SHM because of the reason described above. Various distributed sensing techniques based on Brillouinscattering have been proposed for strain monitoring1-3. Murayama et al. applied Brillouin optical domain reflectometry(BOTDR) to strain monitoring of yacht hulls and at that time the spatial resolution and accuracy were 1 m and ±30 ,
respectively4. Recently Song et al. achieved the spatial resolution of 1.6 mm using Brillouin optical correlation domain
analysis (BOCDA)5. While fiber Bragg gratings (FBGs) with some interrogation systems are ordinarily employed forquasi-distributed strain or temperature measurements, they can be also applied to fully-distributed sensing along FBGs. A
strain distribution along a chirped grating is measured by the phase-based sensing method or the low-coherence
reflectometry6,7. We have developed a distributed strain sensing system using long-length FBGs, based on opticalfrequency domain reflectometry (OFDR)8. We confirmed by simulation that the spatial resolution of this system is lessthan 1 mm9. In this sensing system we employ long-length FBGs whose length is about 100 mm and the sensing region,in other words the gauge length, can be expanded up to 1,500 mm by serially-cascaded long-length FBGs10. These efforts
to improve the spatial resolution of distributed sensing open recent development in the SHM field.

In this paper the distributed sensing system with OFDR is described at first. Then as its application to SHM, strain
monitoring and damage detection for an adhesively bonded joint is shown. Next, in SHM for a wing structure, themeasurement results of the distributed strain monitoring in the composite wing model and load identification based on
distributed strain data are shown.

2. SENSING SYSTEM WIGH OFDRAn arrangement of our sensing system is shown in Fig. 1. The distributed sensing system consists of a tunable laser
source (TLS), two photo-optic detectors (PD1, PD2), three broad band reflectors (R1, R2, R3), three 3dB couplers (C1,C3, C3), three long-length FBGs (FBG1, FBG2, FBG3), an A/D converter (DAQ), and a computer. This arrangement issimilar to the system with OFDR by Childers et al.11, except using the long-length FBGs. When a coherent source scans
R1 and R2 as a function of wavelength or wavenumber, the resultant interference signal from PD1 is obtained and it isused as a trigger signal on DAQ to acquire the interference signal from PD2 at a constant wavenumber. The interference
signal on PD2 is shown in Fig. 2. In this case the length of FBGs was about 100 mm and the interval was 10 mm.

Figure 1. Sensing system.

In our sensing system we use a single processing technique based on short time Fourier transform (STFT) to map thestrain profile along FBGs. In the case that STFT is applied to the interference signal shown in Fig. 2, time and frequency
in usual STFT are corresponding to wavenumber and position, respectively. So by Fourier transform of the data within awindow and sliding the window along the wavenumber axis, we can get a spectrogram as shown in Fig. 3. The horizontal
axis is converted from wavenumber to wavelength and the vertical axis represents the relative position, z, of Fig. 1. The
color depicts the intensity of the reflected light at wavelength, , and position, z. Wavelength spectrum of the reflected
light at an arbitrary position can be extracted from the spectrogram. The spectrum at 4.7 m in Fig. 3 is shown in Fig. 4.
The center wavelength can be determined by calculating the center of the full width at half maximum (FWHM) of thespectrum at each position. Figure 5 shows the center wavelength along FBGs. Finally strain distribution along FBGs isdetermined by the distribution of the center wavelength shift between the initial condition and the current one.

Figure 2. Measured interference signal on PD2.

Figure 3. Spectrogram of measured interference signal.

Figure 4. Spectrum at 4.7 m in spectrogram.

Figure 5. Center wavelength distribution in spectrogram.

3. STRAIN MONITORING OF BONDED JOINT
The use of adhesive bonding in composite structures is recently increasing in aerospace, marine, and automotive sectors
because it has advantages over mechanically fastened joints, such as less source of stress concentrations, more uniform
distribution of load and better fatigue properties12-14. We embedded a long-length FBG whose length is about 90 mm
inside the adhesive of a single-lap joint and measure the strain distribution in the static tensile test. Dimensions of the test
specimen and the location of the FBG sensor are shown in Fig. 6. The specimen is a single-lap joint of two aluminum
palates (aluminum alloy 2017) adhered by epoxy adhesive (Araldite® 2011). The long-length FBG was set on the
V-shaped grooved machined on the aluminum plate. The grating of the region A (40 mm) was bonded on the leftadherend to measure the strain distribution of the left adherend which was outside the overlap region. The region B (30mm) was embedded inside the adhered section of the joint to measure strain distribution along the interface between theadherend and the adhesive. The region C (20 mm) was kept free to be used as reference part for compensation.
The specimen was subjected to static tensile loads and the strain distributions along the FBG were measured. We had
seven load cases and the single-lap joint was broken at the load of 3,920 N as debonding in the case #7. Measured strain
distributions under the tensile loads in #4 and #7 are shown in Fig. 7 and 8, respectively. We confirmed the agreement
between the measured strain in #4 and the calculated one by finite element (FE) model without damage is excellent.
Although it was too difficult to monitor the strain distribution inside the adhesive layer, we could successfully measure it.
In the case #7 distributed profile around the end of overlap differs from the case #4. We also confirmed by using FE
model with damage that debonding at the end of overlap caused the reconstruction strain distributions as shown in Fig. 8.
It is important that we found the strain distribution around the end of overlap depends on the length of debonding,because it might be possible not only to know the existence of damage but also identify the location and type of damage.

Figure 6. Dimensions of specimen and location of FBG sensor.

Figure 7. Strain distributions under the tensile loads (case #4).

Figure 8. Strain distributions under the tensile loads (case #7).

4. SHM FOR WING STRUCTURE
Wings of an aircraft are subjected to a distributed load to lift the body. The load varies depending on kinetic states, suchas flight speed and direction, and environmental conditions, such as atmospheric pressure and its fluctuation, and so on.
Distributed loads of the wings of an in-service aircraft can influence to in-flight safety and fatigue aging. Therefore if weknow the loads of the in-service aircraft, we can increase the in-flight safety and the efficiency of the maintenanceinspection for the aircraft which is designed based on damage tolerance. In general, however, the in-flight load
distribution of a wing cannot be measure directly by sensors. It can be predicted by other structural conditions, such as
strain and displacement, and this problem should be solved by an inverse analysis15,16. We have developed the prediction
technique of the distributed loads on wing structures based on strain distributions measured by fiber-optic distributed
sensors. In this technique, we are using finite element method (FEM) in order to enable integrated and organized
operation of design and in-flight load prediction. In order to investigate the applicability of this technique to SHM, we
implemented distributed strain monitoring of a composite wing structure by using the fiber-optic distributed sensing
system17 and carried out some simulations to confirm the accuracy of load identification by the inverse analysis18.
A composite wing box whose length is approximately 6 m was subjected to a series of load tests as shown in Fig. 9. Twotypes of FBGs were bonded to this structure as shown in Fig. 10. One was line-A, in which multiplexed FBGs with 10
mm length are arrayed in a 100 mm pitch. Seven lines of this type were bonded along the longitudinal direction of thewing in order to measure the overall deformation of the wing box. Each line had about 40 FBGs and the total number of
FBGs was 257. The other was line-B, where a long-length FBG is installed. 14 lines of line-B were fixed adjacent tostress concentration zones where the stiffness is varying discontinuously. The gauge length of B1-B8 was about 300 mm
and that of B9-B14 was about 500 mm. The locations of these sensors were determined based on the stress distribution
calculated by FEM. By using an optical channel selector which had 16 channels, we could monitor the strain
distributions along each FBG line continuously.
In this paper, we show the measured results of Ch.1 and Ch.10. Ch.1 is connected to FBG line A-1, which was bonded
straight along a stringer flange. Ch.10 is connected to FBG line B-3 and B-4, which were fixed along the edge of therectangular area framed by ribs and stringers. Figure 11 shows the strain distributions measured by A-1. The horizontal
axis represents the distance from R3 shown in Fig. 1. The whole length of the sensor array is approximately 4.1 m. The
figure shows that a larger strain occurred at the root of the wing. Moreover, the positions where a less strain occurredcompared to nearby points almost coincided with the positions of ribs. This indicates that the change in the stiffness by
structural reinforcement members was successfully measured. The measured strain showed an almost linear relation withthe applied load. This result shows that the overall deformation of the wing box can be monitored by multiplexed FBG
arrays using our sensing system.
Figure 12 shows the strain distributions measured by B-3 and B-4. Both 300 mm gauge length FBGs were bonded alonga stringer at the front and the rear part, and bonded along a rib at the middle. We can see that tensile strain occurred at

longitudinal directions of the wing whereas compression strain occurred at vertical directions. The amount became larger
with the applied load and the ratio of the tensile and compression strain almost became equal to the Poisson’s ratio. Fromthese results, it can be concluded that the strain distribution of interest could be successfully measured with the highspatial resolution by long-length FBGs using our sensing system.

Figure 9. Composite wing box (left) and test equipment (right).

A-4

A-3

B-9

B-10

B-13

A-7

B-8

B-7

B-6

B-14

B-5

(a) upper side of inner skin(b) upper side of outer skin

B-2

B-1
A-1

B-3

A-6
B-11
B-12

B-4

A-2
(c) lower side of inner skinA-5(d) lower side of outer skin

Figure 10. Sensor location in wing box.

Figure 11. Strain distributions measured by A-1.

Figure 12. Strain distributions measured by B-1 (left) and B4 (right).

Finally we show the technique of load identification based on distributed strain data. Figure 13 shows a finite element
model of the wing box shown in Fig. 9. We assumed that this structure is equipped with fiber-optic distributed strain
sensors. The pressure distribution to be predicted and the pressure distribution predicted without error are shown in Fig.
14 and the agreement between them is excellent. This means that we can reconstruct strain and stress distributions in thewhole wing box by applying the estimated load to the wing in FEM.

zyx

Figure 13. Finite element model of composite wing box.

Figure 14. Pressure distributions to be predicted (left) and predicted (right).

5. CONCLUSIONSIn this paper we described the distributed sensing system with the high spatial resolution by using long-length FBGs andshowed its application to SHM. The efforts to improve the spatial resolution and other functions of distributed sensing
are opening recent development in the SHM field. In order to implement SHM for an in-service structure, we have to
integrate the sensing system, the algorithm assessing the structural integrity, the installation method, and so on into an
SHM system and prove the cost-benefit on maintenance works. This must be interdisciplinary work.

REFERENCES[1] Horiguchi, T., Kurashima, T. and Takeda, M., “Tensile strain dependence of Brillouin frequency shift in silica
optical fiber,” IEEE Photonics Technol. Lett., 1(5), 107-108 (1989).
[2] Bao, X., Brown, A., DeMerchant, M. and Smith, J., “Characterization of the Brillouin-loss spectrum of
single-mode fibers by use of very short (<10-ns) pulses,” Opt. Lett., 24(8), 510-512 (1999).
[3] Hotate, K. and Hasegawa, T., “Measurement of Brillouin gain spectrum distribution along an optical fiber using
a correlation-based technique –proposal, experiment and simulation,” IEICE Trans. Electron., E83-C, 405-412(2000).
[4] Murayama, H., Kageyama, K., Naruse, H., Shimada, A. and Uzawa, K., “Application of fiber-optic distributed
sensors to health monitoring for full-scale composite structures,” J. Intell. Mater. Syst. Struct., 14(1), 3-13 (2003).
[5] Song, K.Y., He, Z., and Hotate, K., “Distributed strain measurement with millimeter-order spatial resolution
based on Brillouin optical correlation domain analysis,” Opt. Lett., 31(17), 2526-2528 (2006).
[6] Volanthen, M., Geiger, H. and Dakin, J.P., “Distributed grating sensors using low-coherence reflectometry,” J.
Lightwave Technol., 15(11), 2076-2082 (1997).
[7] Huang, S., Ohn, M.M. and Measure, R.M., “Phase-based Bragg intragrating distributed strain sensor,” Appl.
Opt., 35(7), 1135-1142 (1996).
[8] Igawa, H., Murayama, H., Kasai, T., Yamaguchi, I., Kageyama, K. and Ohta, K., “Measurements of strain
distribution with a long gauge FBG sensor using optical frequency domain reflectometry,” Proc. SPIE, 5855,
547-550 (2005).
[9] Igawa, H., Ohta, K., Kasai, T., Yamaguchi, I., Murayama, H., and Kageyama, K., “Distributed measurementswith a long gauge FBG sensor using optical frequency domain reflectometry (1st report, system investigation using
optical simulation model),” JSME Int J., Ser. A, 2(9), 1242-1252 (2008).
[10] Igawa, H., Murayama, H., Nakamura, T., Yamaguchi, I., Kageyama, K., Uzawa, K., Wada, D., Ohsawa, I.,
Kanai, M. and Omichi, K., “Measurement of distributed strain and load identification using 1500 mm gauge length
FBG and optical frequency domain reflectometry,” Proc. SPIE, 7503, 750351-1-750351-4 (2009).
[11] Childers, B.A., Froggatt, M.E., Allison, S.G., Moore, T.C., Hare, D.A., Batten, C.F. and Jegley, D.C., "Use of3000 Bragg grating strain sensors distributed on four eight-meter optical fibers during static load tests of acomposite structure," Proc. SPIE, 4332, 133-142 (2001).
[12] Kwakernaak, A. and Hofstede, J.C.J., “Adhesive bonding: providing improved fatigue resistance and damage
tolerance at lower cost,” SAMPE Journal, 44(5), 6-15 (2008).
[13] Cao, J. and Grenstedt, L., “Design and testing of joints for composite sandwich/steel hybrid ship hull,”Composites Part A, 35(9), 1091-1105 (2004).
[14] Fessel, G., Broughton, J.G., Fellows, N.A., Durodola, J.F. and Hutchinson, A.R., “Evaluation of different
lap-shear joint geometries for automotive applications,” Int. J. Adhes. Adhes., 27(7), 574-583 (2007).
[15] Coates, C.W., Thamburai, P. and Kim, C.J., “An inverse method for selection of Fourier coefficients for flightload identification,” AIAA 2005-2183 (2005).
[16] Shkarayev, S., Krashanitsa, R. and Tessler, A., “An inverse interpolation method utilizing in-flight strain
measurements for determining loads and structural response of aerospace vehicles,” Proc. of 3rd IWSHM, 336-343(2001).
[17] Murayama, H., Igawa, H., Yamaguchi, I., Hirano, Y., Aoki, Y., Kageyama, K., Uzawa, K., Akiyama, G., Ohara,K., Nunotani, K., Azemoto, M. and Omichi, K., “Distributed strain monitoring of composite wing structure by
FBG sensors,” 13th US-Japan Conference on Composite Materials, CD-ROM (2008).
[18] Murayama, H., Akiyama, G., Igawa, H., Nakamura, T., Kageyama, K., Uzawa, K., Hirano, Y. and Aoki, Y.,“Application of inverse analysis of distributed load with strain sensors to wing structures,” Structural Health
Monitoring 2009, DEStech Publications, Inc., 75-82 (2009).