An effective approach to structural damage localization in exural members based on generalized S-transform

Document Type : Article

Authors

1 Department of Civil Engineering, Sharif University of Technology, Tehran, P.O. Box 11155-9313 Tehran, Iran.

2 School of Civil Engineering, Iran University of Science & Technology, Tehran, Iran.

Abstract

This paper presents a method for structural damage localization based on signal processing using generalized S-transform (SGS). The S-transform is the combinations of the properties of the short-time Fourier transform (STFT) and wavelet transform (WT) that has been developed over the last few years in an attempt to overcome inherent limitations of the wavelet and short time Fourier transform in Time-Frequency representation of non-stationary signals. The generalized type of this transform is the SGS-transform that has adjustable Gaussian window width in the time-frequency representation of signals. In this research, the SGS-transform has been employed due to its favorable performance in detection of the structural damages. The performance of the proposed method has been verified by means of three numerical examples and also the experimental data obtained from the vibration test of 8-DOFs mass–stiffness system. By way of the comparison between damage location obtained from the proposed method and simulation model, it was concluded that the method is sensitive to the damage existence and clearly demonstrates the damage location.

Keywords

Main Subjects


1. Amezquita-Sanchez, J.P. and Adeli, H. Signal processing techniques for vibration-based health monitoring of smart structures", Archives of Computational Methods in Engineering, 23(1), pp. 1-15 (2016). 2. Doebling, S.W., Farrar, C.R., Prime, M.B., and Shevitz, D.W., Damage Identi_cation and Health Monitoring of Structural and Mechanical Systems from Changes in Their Vibration Characteristics: A Liter3138 H. Amini Tehrani et al./Scientia Iranica, Transactions A: Civil Engineering 26 (2019) 3125{3139 ature Review, Los Alamos National Lab., NM, United States (1996). 3. Sohn, H., Farrar, C.R., Hemez, F.M., Shunk, D.D., Stinemates, D.W., Nadler, B.R., and Czarnecki, J.J., A Review of Structural Health Monitoring Literature: 1996-2001, Los Alamos National Laboratory, Los Alamos, New Mexico (2002). 4. Ditommaso, R. Mucciarelli, M., and Ponzo, F.C. S-Transform based _lter applied to the analysis of non-linear dynamic behaviour of soil and buildings", Conference Proceeding, Republic of Macedonia (2010). 5. Ditommaso, R., Parolai, S., Mucciarelli, M., Eggert, S., Sobiesiak, M., and Zschau, J. Monitoring the response and the back-radiated energy of a building subjected to ambient vibration and impulsive action: The falkenhof tower (Potsdam, Germany) ", Bulletin of Earthquake Engineering, 8(3), pp. 705-722 (2010). 6. Gabor, D. Theory of communication. Part 1: The analysis of information", Journal of the Institution of Electrical Engineers, 93(26), pp. 429-441 (1946). 7. Portno_, M. Time-frequency representation of digital signals and systems based on short-time Fourier analysis", IEEE Transactions on Acoustics, Speech, and Signal Processing, 28(1), pp. 55-69 (1980). 8. Bloom_eld, P., Fourier Analysis of Time Series: An Introduction, John Wiley & Sons (2004). 9. Cohen, L. Time-frequency distributions-a review", Proceedings of the IEEE, 77(7), pp. 941-981 (1989). 10. Ovanesova, A. and Suarez, L. Applications of wavelet transforms to damage detection in frame structures", Engineering Structures, 26(1), pp. 39-49 (2004). 11. Ren, W.X. and Sun, Z.S. Structural damage identi_- cation by using wavelet entropy", Engineering Structures, 30(10), pp. 2840-2849 (2008). 12. Cao, M., Xu, W., Ostachowicz, W., and Su, Z. Damage identi_cation for beams in noisy conditions based on Teager energy operator-wavelet transform modal curvature", Journal of Sound and Vibration, 333(6), pp. 1543-1553 (2014). 13. Kaloop, M.R. and Hu, J.W. Damage identi_cation and performance assessment of regular and irregular buildings using wavelet transform energy", Advances in Materials Science and Engineering, 2016, pp. 1-11, Article ID: 6027812, Hindawi (2016). 14. Janeliukstis, R., Rucevskis, S., Akishin, P., and Chate, A. Wavelet transform based damage detection in a plate structure", Procedia Engineering, 161, pp. 127- 132 (2016). 15. Balafas, K., Kiremidjian, A.S., and Rajagopal, R. The wavelet transform as a Gaussian process for damage detection", Structural Control and Health Monitoring, 25(2), pp. 1-20 (2017). 16. Stockwell, R. Why use the S-transform. AMS pseudodi _erential operators: Partial di_erential equations and time-frequency analysis", Fields Institute Communications, 52, pp. 279-309 (2007). 17. Stockwell, R., Mansinha, L., and Lowe, R. Localization of the complex spectrum: the S transform", IEEE Transactions on Signal Processing, 44(4), pp. 998-1001 (1996). 18. Bindi, D., Parolai, S., Cara, F., Di Giulio, G., Ferretti, G., Luzi, L., Monachesi, G., Pacor, F., and Rovelli, A. Site ampli_cations observed in the Gubbio basin, central Italy: hints for lateral propagation e_ects", Bulletin of the Seismological Society of America, 99(2A), pp. 741-760 (2009). 19. Parolai, S. Denoising of seismograms using the Stransform", Bulletin of the Seismological Society of America, 99(1), pp. 226-234 (2009). 20. Pakrashi, V. and Ghosh, B. Application of Stransform in structural health monitoring", 7th International Symposium on Nondestructive Testing in Civil Engineering (NDTCE), Nantes, France (2009). 21. Ditommaso, R., Mucciarelli, M., Parolai, S., and Picozzi, M. Monitoring the structural dynamic response of a masonry tower: Comparing classical and timefrequency analyses", Bulletin of Earthquake Engineering, 10(4), pp. 1221-1235 (2012). 22. Ditommaso, R., Mucciarelli, M., and Ponzo, F.C. Analysis of non-stationary structural systems by using a band-variable _lter", Bulletin of Earthquake Engineering, 10(3), pp. 895-911 (2012). 23. Ditommaso, R., Ponzo, F., and Auletta, G. Damage detection on framed structures: modal curvature evaluation using Stockwell transform under seismic excitation", Earthquake Engineering and Engineering Vibration, 14(2), pp. 265-274 (2015). 24. Addison, P.S., The Illustrated Wavelet Transform Handbook: Introductory Theory and Applications in Science, Engineering, Medicine and Finance, CRC Press (2017). 25. Mallat, S., A Wavelet Tour of Signal Processing, San Diego, Academic Press (1999). 26. Stockwell, R. A basis for e_cient representation of the S-transform", Digital Signal Processing, 17(1), pp. 371-393 (2007). 27. Pinnegar, C. and Mansinha, L. Time-local Fourier analysis with a scalable, phase-modulated analyzing function: The S-transform with a complex window", Signal Processing, 84(7), pp. 1167-1176 (2004). 28. Wang, Y., The Tutorial: S-Transform, Graduate Institute of Communication Engineering, National Taiwan University, Taipei (2010). 29. Alwash, M., Sparling, B.F., and Wegner, L.D. Inuence of excitation on dynamic system identi_cation for a multi-span reinforced concrete bridge", Advances in Civil Engineering, 2009, pp. 1-18, Article ID: 859217, Hindawi (2009). H. Amini Tehrani et al./Scientia Iranica, Transactions A: Civil Engineering 26 (2019) 3125{3139 3139 30. Du_ey, T.A., Doebling, S.W., Farrar, C.R., Baker, W.E., and Rhee, W.H. Vibration-based damage identi _cation in structures exhibiting axial and torsional response", Journal of Vibration and Acoustics, 123(1), pp. 84-91 (2001).