Structural Engineering and Mechanics

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A direct damage detection method using Multiple Damage Localization Index Based on Mode Shapes criterion

  • Homaei, F. (School of Civil Engineering, Iran University of Science & Technology) ;
  • Shojaee, S. (Department of Civil Engineering, Shahid Bahonar University) ;
  • Amiri, G. Ghodrati (School of Civil Engineering, Iran University of Science & Technology)
  • Received : 2012.06.14
  • Accepted : 2013.12.09
  • Published : 2014.01.25
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Abstract

A new method of multiple damage detection in beam like structures is introduced. The mode shapes of both healthy and damaged structures are used in damage detection process (DDP). Multiple Damage Localization Index Based on Mode Shapes (MDLIBMS) is presented as a criterion in detecting damaged elements. A finite element modeling of structures is used to calculate the mode shapes parameters. The main advantages of the proposed method are its simplicity, flexibility on the number of elements and so the accuracy of the damage(s) position(s), sensitivity to small damage extend, capability in prediction of required number of mode shapes and low sensitivity to noisy data. In fact, because of differential and comparative form of MDLIBMS, using noise polluted data doesn't have major effect on the results. This makes the proposed method a powerful one in damage detection according to measured mode shape data. Because of its flexibility, damage detection process in multi span bridge girders with non-prismatic sections can be done by this method. Numerical simulations used to demonstrate these advantages.

Keywords

References

  1. Jeyasehar, A.C. and Sumangala, K. (2006), "Damage assessment of prestressed concrete beams using artificial neaural network (ANN) approach", Comput. Struct., 84, 1709-1718. https://doi.org/10.1016/j.compstruc.2006.03.005
  2. Bagheri, A., Ghodrati Amiri, G. and Seyed Razzaghi, S.A. (2009), "Vibration-based damage identification of plate structures via curvelet transform", J. Sound Vib., 327, 593-603. https://doi.org/10.1016/j.jsv.2009.06.019
  3. Beena, P. and Ganguli, R. (2011), "Structural damage detection using fuzzy cognitive maps and Hebbian learning", Appl. Soft Comput., 11, 1014-1020. https://doi.org/10.1016/j.asoc.2010.01.023
  4. Danai, K., Civjan, S.A. and Styckiewicz, M. (2012), "Direct method of damage localization for civil structures via shape comparison of dynamic response measurements", Comput. Struct., 92-93, 297-307. https://doi.org/10.1016/j.compstruc.2011.10.016
  5. Esfandiari, A., Bakhtiari Nejad, F., Sanayei, M. and Rahai, A. (2010), "Structural finite element model updating using transfer function data", Comput. Struct., 88, 54-64. https://doi.org/10.1016/j.compstruc.2009.09.004
  6. Esfandiari, E., Bakhtiari Nejad, F., Rahai, A. and Sanayei, M. (2009), "Structural model updating using frequency response function and quasi-linear sensitivity equation", J. Sound Vib., 326, 557-573. https://doi.org/10.1016/j.jsv.2009.07.001
  7. Friswell, M.I., Penny, J.E. and Garvey, S.D. (1998), "A combined genetic and eigensensitivity algorithm for the location of damage in structures", Comput. Struct., 69, 547-556. https://doi.org/10.1016/S0045-7949(98)00125-4
  8. Gou, H. and Ling, Z. (2006), "A weighted balance evidence theory for structural multiple damage localization", Comput. Method. Appl. Mech. Eng., 195, 6225-6238. https://doi.org/10.1016/j.cma.2005.12.010
  9. Guan, H. and Karbhari, V. (2008), "Improved damage detection method based on Element Modal Strain Damage Index using sparse measurement", J. Sound Vib., 309, 465-494. https://doi.org/10.1016/j.jsv.2007.07.060
  10. He, R. and Hwang, S. (2007), "Damage detection by a hybrid real-parameter genetic algorithm under the assistance of grey relation analysis", Eng. Appl. Artif. Intel., 20, 980-992. https://doi.org/10.1016/j.engappai.2006.11.020
  11. Jiang, S.F., Zhang, C.M. and Zhang, S. (2011), "Two-stage structural damage detection using fuzzy neural networks and data fusion techniques", Exp. Syst. Appl., 38, 511-519. https://doi.org/10.1016/j.eswa.2010.06.093
  12. Khorshidian, F. and Esfandiari, A. (2011), "Structural damage diagnosis using modal data", Scientia Iranica, 18 (4), 853-860. https://doi.org/10.1016/j.scient.2011.07.012
  13. Koh, B.H. and Dyke, S.J. (2007), "Structural health monitoring for flexible bridge structures using correlation and sensitivity of modal data", Comput. Struct., 85, 117-130. https://doi.org/10.1016/j.compstruc.2006.09.005
  14. Lakshmi Narayana, K. and Jebaraj, C. (1999), "Sensitivity analysis of local/global modal parameters for identification of a crack in a beam", J. Sound Vib., 228(5), 977-994. https://doi.org/10.1006/jsvi.1999.2445
  15. Lee, U. and Shin, J. (2002), "A frequency response function-based structural damage identification method", Comput. Struct., 80, 117-132. https://doi.org/10.1016/S0045-7949(01)00170-5
  16. Li, Y.Y. and Chen, Y. (2013), "A review on recent development of vibration-based structural robust damage detection", Struct. Eng. Mech., 45(2). 159-168. https://doi.org/10.12989/sem.2013.45.2.159
  17. Liu, X., Lieven, N.A. and Escamilla-Ambrosio, P.J. (2009), "Frequency response function shape-based method for structural damage localization", Mech. Syst. Sig. Proc., 23, 1243-1259. https://doi.org/10.1016/j.ymssp.2008.10.002
  18. Messina, A., Williams, E.J. and Contursi, T. (1998), "Structural damage detection by sensitivity and statistical-based method", J. Sound Vib, 216(5), 791-808. https://doi.org/10.1006/jsvi.1998.1728
  19. Morassi, A. and Vestroni, F. (2008), Dynamic Methods for Damage Detection in Structures, Springer Wien New York.
  20. Na, C., Kim, S.P. and Kwak, H.G. (2011), "Structural damage evaluation using genetic algorithm", J. Sound Vib, 330, 2772-2783. https://doi.org/10.1016/j.jsv.2011.01.007
  21. Nobahari, M. and Seyedpoor, S.M. (2011), "Structural damage detection using an efficient correlation-based index and a modified genetic algorithm", Math. Comput. Model., 53, 1798-1809. https://doi.org/10.1016/j.mcm.2010.12.058
  22. Pandey, A.K., Biswas, M. and Samman, M.M. (1991), "Damage detection from changes in curvature mode shapes", J. Sound Vib., 145(2), 321-332. https://doi.org/10.1016/0022-460X(91)90595-B
  23. Radzienski, M., Krawczuk, M. and Palacz, M. (2011), "Improvement of damage detection methods based on experimental modal parameters", Mech. Syst. Sig. Proc., 25, 2169-2190. https://doi.org/10.1016/j.ymssp.2011.01.007
  24. Sampaio, R.P., Maia, N.M. and Silva, J.M. (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
  25. Seyedpoor, S.M. (2012), "A two stage method for structural damage detection using a modal strain energy based index and particle swarm optimization", Int. J. Nonlin. Mech., 47, 1-8.
  26. Shi, Z.Y., Law, S.S. and Zhang, L.M. (2000), "Damage localization by directly using incomplete mode shapes", J. Eng. Mech., 126(6), 656-660. https://doi.org/10.1061/(ASCE)0733-9399(2000)126:6(656)
  27. Stubbs, N., Kim, J.T. and Charles, R.F. (1995), "Field verification of a nondestructive damage localization and severity estimation algorithm", Proceedings XIII International Modal Analysis Conference, Nashville, U.S.A.
  28. Wu, N. and Wang, Q. (2011), "Experimental studies on damage detection of beam structures with wavelet transform", Int. J. Eng. Sci., 49, 253-261. https://doi.org/10.1016/j.ijengsci.2010.12.004
  29. Yu, Z. and Jianwei, Z. (2010), "Damage identification of a concrete cantilever beam based on elman neural network", Proceedings of 2010 International Conference on Computer Application and System Modeling (ICCASM 2010).

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