Smart Structures and Systems

Techno-Press (테크노프레스)
권호 표지
DOI QR코드

DOI QR Code

Damage detection in plate structures using frequency response function and 2D-PCA

  • Khoshnoudian, Faramarz (Faculty of Civil Engineering, Amirkabir University of Technology (Tehran Polytechnic)) ;
  • Bokaeian, Vahid (Faculty of Civil Engineering, Amirkabir University of Technology (Tehran Polytechnic))
  • Received : 2016.12.21
  • Accepted : 2017.08.22
  • Published : 2017.10.25
⟨ Previous Next ⟩

Abstract

One of the suitable structural damage detection methods using vibrational characteristics are damage-index-based methods. In this study, a damage index for identifying damages in plate structures using frequency response function (FRF) data has been provided. One of the significant challenges of identifying the damages in plate structures is high number of degrees of freedom resulting in decreased damage identifying accuracy. On the other hand, FRF data are of high volume and this dramatically decreases the computing speed and increases the memory necessary to store the data, which makes the use of this method difficult. In this study, FRF data are compressed using two-dimensional principal component analysis (2D-PCA), and then converted into damage index vectors. The damage indices, each of which represents a specific condition of intact or damaged structures are stored in a database. After computing damage index of structure with unknown damage and using algorithm of lookup tables, the structural damage including the severity and location of the damage will be identified. In this study, damage detection accuracy using the proposed damage index in square-shaped structural plates with dimensions of 3, 7 and 10 meters and with boundary conditions of four simply supported edges (4S), three clamped edges (3C), and four clamped edges (4C) under various single and multiple-element damage scenarios have been studied. Furthermore, in order to model uncertainties of measurement, insensitivity of this method to noises in the data measured by applying values of 5, 10, 15 and 20 percent of normal Gaussian noise to FRF values is discussed.

Keywords

References

  1. Balageas, D., Fritzen, C.-P. and Guemes, A. (2006), Structural Health Monitoring, Wiley Online Library, London, UK.
  2. Chen, B. and Xu, Y. (2007), "A new damage index for detecting sudden change of structural stiffness", Struct. Eng. Mech., 26(3), 315-341. https://doi.org/10.12989/sem.2007.26.3.315
  3. Chopra, A.K. (1995), Dynamics of Structures, Prentice Hall, New Jersey, USA.
  4. Choudhury, A.R. (1996), "Damage detection in structures using measured frequency response function data", Ph.D. Dissertation; Victoria University of Technology, Melbourne, Australia.
  5. Esfandiari, A., Bakhtiari-Nejad, F. and Rahai, A. (2013), "Theoretical and experimental structural damage diagnosis method using natural frequencies through an improved sensitivity equation", Int. J. Mech. Sci., 70 79-89. https://doi.org/10.1016/j.ijmecsci.2013.02.006
  6. Fan, W. and Qiao, P. (2012), "A strain energy-based damage severity correction factor method for damage identification in plate-type structures", Mech. Syst. Signal Pr., 28 660-678. https://doi.org/10.1016/j.ymssp.2011.11.010
  7. Fang, X., Luo, H. and Tang, J. (2005), "Structural damage detection using neural network with learning rate improvement", Comput. Struct., 83(25), 2150-2161. https://doi.org/10.1016/j.compstruc.2005.02.029
  8. Gomes, H. and Silva, N. (2008), "Some comparisons for damage detection on structures using genetic algorithms and modal sensitivity method", Appl. Math. Model., 32(11), 2216-2232. https://doi.org/10.1016/j.apm.2007.07.002
  9. Huh, Y.C., Chung, T.Y., Lee, J.W. and Kim, J.K. (2015), "Damage identification in plates using vibratory power estimated from measured accelerations", J. Sound Vib., 336 106-131. https://doi.org/10.1016/j.jsv.2014.10.003
  10. Huynh, D., He, J. and Tran, D. (2005), "Damage location vector: A non-destructive structural damage detection technique", Comput. Struct., 83(28), 2353-2367. https://doi.org/10.1016/j.compstruc.2005.03.029
  11. Khoshnoudian, F. and Talaei, S. (2016), "A new damage index using FRF data, 2D-PCA method and pattern recognition techniques", Int. J. Struct. Stab. Dy., 1750090.
  12. Khoshnoudian, F., Talaei, S. and Fallahian, M. (2016), "Structural damage detection using FRF data, 2D-PCA, artificial neural networks and imperialist competitive algorithm simultaneously", Int. J. Struct. Stab. Dy., 1750073.
  13. Moaveni, B., Lombaert, G., Stavridis, A., Conte, J.P. and Shing, P. B. (2011), "Damage identification of a three-story infilled RC frame tested on the UCSD-NEES shake table", Dynam. Civil Struct., 4, Springer: 145-154.
  14. Sampaio, R., Maia, N. and Silva, J. (1999), "Damage detection using the frequency-response-function curvature method", J. Sound Vib., 226(5), 1029-1042. https://doi.org/10.1006/jsvi.1999.2340
  15. Shadan, F., Khoshnoudian, F. and Esfandiari, A. (2016a), "A frequency response-based structural damage identification using model updating method", Struct. Control Health., 23(2), 286-302. https://doi.org/10.1002/stc.1768
  16. Shadan, F., Khoshnoudian, F., Inman, D.J. and Esfandiari, A. (2016b), "Experimental validation of a FRF-based model updating method", J. Vib. Control, 1077546316664675.
  17. Trendafilova, I. and Heylen, W. (2003), "Categorisation and pattern recognition methods for damage localisation from vibration measurements", Mech. Syst. Signal Pr., 17(4), 825-836. https://doi.org/10.1006/mssp.2002.1518
  18. Vo-Duy, T., Ho-Huu, V., Dang-Trung, H., Dinh-Cong, D. and Nguyen-Thoi, T. (2016), "Damage Detection in Laminated Composite Plates Using Modal Strain Energy and Improved Differential Evolution Algorithm", Procedia Eng., 142, 181-188.
  19. Xiang, J. and Liang, M. (2012), "A two-step approach to multidamage detection for plate structures", Eng. Fract. Mech., 91 73-86. https://doi.org/10.1016/j.engfracmech.2012.04.028
  20. Xu, W., Cao, M., Ostachowicz, W., Radzienski, M. and Xia, N. (2015), "Two-dimensional curvature mode shape method based on wavelets and Teager energy for damage detection in plates", J. Sound Vib., 347 266-278. https://doi.org/10.1016/j.jsv.2015.02.038
  21. Yam, L., Li, Y. and Wong, W. (2002), "Sensitivity studies of parameters for damage detection of plate-like structures using static and dynamic approaches", Eng. Struct., 24(11), 1465-1475. https://doi.org/10.1016/S0141-0296(02)00094-9
  22. Yang, J., Zhang, D., Frangi, A.F. and Yang, J.Y. (2004), "Twodimensional PCA: a new approach to appearance-based face representation and recognition", IEEE T. Pattern Anal., 26(1), 131-137. https://doi.org/10.1109/TPAMI.2004.1261097
  23. Zang, C. and Imregun, M. (2001), "Combined neural network and reduced FRF techniques for slight damage detection using measured response data", Arch. Appl. Mech., 71(8), 525-536. https://doi.org/10.1007/s004190100154
  24. Zhang, Y., Wang, L., Lie, S.T. and Xiang, Z. (2013), "Damage detection in plates structures based on frequency shift surface curvature", J. Sound Vib., 332(25), 6665-6684. https://doi.org/10.1016/j.jsv.2013.07.028

Cited by

  1. Structural damage detection in plates using a deep neural network-couple sparse coding classification ensemble method vol.27, pp.3, 2017, https://doi.org/10.1177/1077546320929156