Vibration-Based Damage Detection of Bridges under Varying Temperature Effects Using Time-Series Analysis and Artificial Neural Networks
Publication: Journal of Bridge Engineering
Volume 22, Issue 10
Abstract
Structural health monitoring (SHM) has become a very important research area for evaluating the performances of bridges. An important issue with continuous SHM and damage detection of bridges is the effects of temperature variations on the measurement data, which can produce bigger effects in the response than the damage itself. In this study, a sensor-clustering-based time-series analysis method integrated with artificial neural networks (ANNs) was employed for damage detection under temperature variations. The damage features obtained solely using the time-series-based damage-detection algorithm are very effective for damage assessment; however, they yield false positives and negatives when temperature variations are present. Therefore, ANNs were used to compensate the temperature effects on the damage features obtained from time-series analysis. This methodology is applied to a footbridge finite-element model in which 2,000 simulations with temperature effects and damage cases were conducted. Results reveal that the proposed method can successfully determine the existence, location, and relative severity of damage using output-only vibration and temperature data even when temperature variations are present.
Get full access to this article
View all available purchase options and get full access to this article.
References
AASHTO. (2010). “Bridge design specifications, customary U.S. units.” AASHTO LRFD, 5th Ed.
Alampalli, S. (1998). “Influence of in-service environment on modal parameters.” Proc., 16th Annual International Modal Analysis Conference, International Society for Optics and Photonics, Bellingham, WA, 111–116.
Baptista, F. G., Budoya, D. E., de Almeida, V. A. D., and Ulson, J. A. C. (2014). “An experimental study on the effect of temperature on piezoelectric sensors for impedance-based structural health monitoring.” Sensors, 14(1), 1208–1227.
Barr, P. J., Stanton, J. F., and Eberhard, M. O. (2005). “Effects of temperature variations on precast, prestressed concrete bridge girders.” J. Bridge Eng., 186–194.
Box, G. E., Jenkins, G. M., and Reinsel, G. C. (2013). Time series analysis: Forecasting and control, 4th Ed., John Wiley & Sons, Hoboken, NJ.
Brownjohn, J. M. W., de Stefano, A., Xu, Y. L., Wenzel, H., and Aktan, A. E. (2011). “Vibration-based monitoring of civil infrastructure: Challenges and successes.” J. Civ. Struct. Health Monit., 1(3), 79–95.
BSI Group. (2006). “Steel, concrete and composite bridges. Specification for loads.” BS 5400-2.
CSA Group. (2006). “Canadian highway bridge design code.” CAN/CSA-S6-06.
Catbas, F. N., Susoy, M., and Frangopol, D. M. (2008). “Structural health monitoring and reliability estimation: Long span truss bridge application with environmental monitoring data.” Eng. Struct., 30(9), 2347–2359.
Comanducci, G., Ubertini, F., and Materazzi, A. L. (2015). “Structural health monitoring of suspension bridges with features affected by changing wind speed.” J. Wind Eng. Ind. Aerodyn., 141(Jun), 12–26.
Cornwell, P., Farrar, C. R., Doebling, S. W., and Sohn, H. (1999). “Environmental variability of modal properties.” Exp. Tech., 23(6), 45–48.
Cross, E. J., Koo, K. Y., Brownjohn, J. M. W., and Worden, K. (2013). “Long-term monitoring and data analysis of the Tamar Bridge.” Mech. Syst. Sig. Process, 35(Feb), 16–34.
Deraemaeker, A., Reynders, E., De Roeck, G., and Kullaa, J. (2008). “Vibration-based structural health monitoring using output-only measurements under changing environment.” Mech. Syst. Sig. Process., 22(1), 34–56.
Deutsches Institut Fur Normung E.V. (1985). “Road and foot bridges—design loads.” DIN 1072 (German national standard).
Doebling, S. W., Farrar, C. R., Prime, M. B., and Cornwell, P. J., (2000). “Structural health monitoring studies of the Alamosa Canyon and I-40 bridges.” Los Alamos National Laboratory Rep. LA-13635-MS, Los Alamos National Laboratory, Los Alamos, NM.
Doebling, S. W., Farrar, C. R., Prime, M. B., and Shevitz, D. W. (1996). “Damage identification and health monitoring of structural and mechanical systems from changes in their vibration characteristics: A literature review.” Los Alamos National Laboratory Rep. LA-13070-MS, Los Alamos National Laboratory, Los Alamos, NM.
Farrar, C. R., and James, G. H. (1997). “System identification from ambient vibration measurements on a bridge.” J. Sound Vib., 205(1), 1–18.
Figueiredo, E., Park, G., Farrar, C. R., Worden, K., and Figueiras, J. (2011). “Machine learning algorithms for damage detection under operational and environmental variability.” Struct. Health Monit., 10(6), 559–572.
Follen, C. W., Sanayei, M., Brenner, B. R., and Vogel, R. M. (2014). “Statistical bridge signatures.” J. Bridge Eng., 04014022.
Fu, Y., and DeWolf, J. T. (2001). “Monitoring and analysis of a bridge with partially restrained bearings.” J. Bridge Eng., 23–29.
Gül, M. (2009). “Investigation of damage detection methodologies for structural health monitoring.” Ph.D. dissertation, Univ. of Central Florida, Orlando, FL.
Gül, M., and Catbas, F. N. (2011a). “Damage assessment with ambient vibration data using a novel time series analysis methodology.” J. Struct. Eng., 1518–1526.
Gül, M., and Çatbaş, F. N. (2011b). “Structural health monitoring and damage assessment using a novel time series analysis methodology with sensor clustering.” J Sound Vib., 330(6), 1196–1210.
He, X. (2008). “Vibration-based damage identification and health monitoring of civil structures.” Ph.D. thesis, Univ. of California, Dept. of Structural Engineering, San Diego.
Hong, D.-S., Nguyen, K.-D., Lee, I.-C., and Kim, J.-T. (2012). “Temperature-compensated damage monitoring by using wireless acceleration-impedance sensor nodes in steel girder connection.” Int. J. Distrib. Sens. Netw., 8(9), 167120.
Hsu, T.-Y., and Loh, C.-H. (2010). “Damage detection accommodating non-linear environmental effects by non-linear principal component analysis.” Struct. Control Health Monit., 17(3), 338–354.
Hu, W. H., Thöns, S., Rohrmann, R. G., Said, S., and Rücker, W. (2015). “Vibration-based structural health monitoring of a wind turbine system Part II: Environmental/operational effects on dynamic properties.” Eng. Struct., 89, 273–290.
Khanukhov, K. M., Polyak, V. S., Avtandilyan, G. I., and Vizir, P. L. (1986). Dynamic elasticity modulus for low-carbon steel in the climactic temperature range, Vol. 7, Central Scientific-Research Institute of Designing Steel Structures, Moscow, 55–58.
Ko, J. M., and Ni, Y. Q. (2005). “Technology developments in structural health monitoring of large-scale bridges.” Eng. Struct., 27(12), 1715–1725.
Koo, K. Y., Brownjohn, J. M. W., List, D. I., and Cole, R. (2013). “Structural health monitoring of the Tamar suspension bridge.” Struct. Control Health Monit., 20(4), 609–625.
Kostić, B. (2015). “A framework for vibration based damage detection of bridges under varying temperature effects using artificial neural networks and time series analysis.” M.Sc. thesis, Univ. of Alberta, Edmonton, AB, Canada.
Kostić, B., and Gül, M. (2014). “Damage assessment of a laboratory bridge model using time series analysis.” Proc., 9th Int. Conf. on Short and Medium Span Bridges, Canadian Society for Civil Engineering, Montreal, Canada.
Kostić, B., and Gül, M. (2015). “Damage detection under varying temperature influence using artificial neural networks and time series analysis methods.” 10th Int. Workshop on Structural Health Monitoring (IWSHM), Stanford Univ., Stanford, CA.
Kromanis, R., and Kripakaran, P. (2014). “Predicting thermal response of bridges using regression models derived from measurement histories.” Comput. Struct., 136(May), 64–77.
Kullaa, J. (2014). “Structural health monitoring under nonlinear environmental or operational influences.” Shock Vib., 2014, 863494.
Laory, I., Trinh, T. N., Smith, I. F. C., and Brownjohn, J. M. W. (2014). “Methodologies for predicting natural frequency variation of a suspension bridge.” Eng. Struct., 80, 211–221.
Li, H., Li, S. L., Ou, J. P., and Li, H. W. (2010). “Modal identification of bridges under varying environmental conditions: Temperature and wind effects.” Struct. Control Health Monit., 17(5), 499–512.
Liu, C., Harley, J. B., Bergés, M., Greve, D. W., and Oppenheim, I. J. (2015). “Robust ultrasonic damage detection under complex environmental conditions using singular value decomposition.” Ultrasonics, 58(Apr), 75–86.
Ljung, L. (1999). System identification: Theory for the user, 2nd Ed., Prentice Hall, Upper Saddle River, NJ.
Meruane, V., and Heylen, W. (2012). “Structural damage assessment under varying temperature conditions.” Struct. Health Monit., 11(3), 345–357.
Moorty, S., and Roeder, C. W. (1992). “Temperature-dependent bridge movements.” J. Struct. Eng., 1090–1105.
Mosavi, A. A., Seracino, R., and Rizkalla, S. (2012). “Effect of temperature on daily modal variability of a steel-concrete composite bridge.” J. Bridge Eng., 979–983.
Moser, P., and Moaveni, B. (2011). “Environmental effects on the identified natural frequencies of the Dowling Hall Footbridge.” Mech. Syst. Sig. Process., 25(7), 2336–2357.
Oh, C. K., and Sohn, H. (2009). “Damage diagnosis under environmental and operational variations using unsupervised support vector machine.” J. Sound Vib., 325(Aug), 224–239.
Peeters, B., and De Roeck, G. (2001). “One-year monitoring of the Z24-Bridge: Environmental effects versus damage events.” Earthquake Eng. Struct. Dyn., 30(2), 149–171.
Reynders, E., Wursten, G., and De Roeck, G. (2014). “Output-only structural health monitoring in changing environmental conditions by means of non-linear system identification.” Struct. Health Monit., 13(1), 82–93.
Sabeur, H., Colina, H., and Bejjani, M. (2007). “Elastic strain, Young’s modulus variation during uniform heating of concrete.” Mag. Concr. Res., 59(8), 559–566.
Samali, B., Dackermann, U., and Li, J. (2012). “Location and severity identification of notch-type damage in a two-storey framed structure utilising frequency response functions and artificial neural networks.” Adv. Struct. Eng., 15(5), 743–757.
Santos, A., Figueiredo, E., Silva, M. F. M., Sales, C. S., and Costa, J. C. W. A. (2016). “Machine learning algorithms for damage detection: Kernel-based approaches.” J. Sound Vib., 363(Feb), 584–599.
Sepehry, N., Shamshirsaz, M., and Bastani, A. (2011). “Experimental and theoretical analysis in impedance-based structural health monitoring with varying temperature.” Struct. Health Monit., 10(6), 573–585.
Sohn, H. (2007). “Effects of environmental and operational variability on structural health monitoring.” Phil. Trans. R. Soc. London, Ser. A, 365(1851), 539–560.
Sohn, H., Park, G., Wait, J. R., Limback, N. P., and Farrar, C. R. (2004). “Wavelet-based active sensing for delamination detection in composite structures.” Smart Mater. Struct., 13(1), 153–160.
Sohn, H., Worden, K., and Farrar, C. R. (2002). “Statistical damage classification under changing environmental and operational conditions.” J. Intell. Mater. Syst. Struct., 13(9), 561–574.
Torres-Arredondo, M.-A., Sierra-Pérez, J., Tibaduiza, D.-A., Mcgugan, M., Rodellar, J., and Fritzen, C.-P. (2015). “Signal-based nonlinear modelling for damage assessment under variable temperature conditions by means of acousto-ultrasonics.” Struct. Control Health Monit., 22(8), 1103–1118.
Xu, Z. D., and Wu, Z. (2007). “Simulation of the effect of temperature variation on damage detection in a long-span cable-stayed bridge.” Struct. Health Monit., 6(3), 177–189.
Yan, A. M., Kerschen, G., De Boe, P., and Golinval, J. C. (2005). “Structural damage diagnosis under changing environmental conditions—Part II: Local PCA for non-linear cases.” J. Mech. Syst. Sig. Process., 19(4), 865–880.
Yarnold, M. T. and Moon, F. L. (2015). “Temperature-based structural health monitoring baseline for long-span bridges.” Eng. Struct., 86, 157–167.
Zhou, H. F., Ni, Y. Q., and Ko, J. M. (2012). “Eliminating temperature effect in vibration-based structural damage detection.” J. Eng. Mech., 785–796.
Zhou, L., Xia, Y., Brownjohn, J. M. W., and Koo, K. Y. (2016). “Temperature analysis of a long-span suspension bridge based on field monitoring and numerical simulation.” J. Bridge Eng., 04015027.
Information & Authors
Information
Published In
Journal of Bridge Engineering
Volume 22 • Issue 10 • October 2017
Copyright
© 2017 American Society of Civil Engineers.
History
Received: Apr 5, 2016
Accepted: Mar 16, 2017
Published online: Jul 21, 2017
Published in print: Oct 1, 2017
Discussion open until: Dec 21, 2017
Authors
Metrics & Citations
Metrics
Citations
Download citation
If you have the appropriate software installed, you can download article citation data to the citation manager of your choice. Simply select your manager software from the list below and click Download.