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Damage detection using both energy and displacement damage index on the ASCE benchmark problem

  • Khosraviani, Mohammad Javad (Department of Civil Engineering, Qazvin Branch, Islamic Azad University) ;
  • Bahar, Omid (Department of Structural Engineering Research Center, International Institute of Earthquake Engineering and Seismology (IIEES)) ;
  • Ghasemi, Seyed Hooman (Department of Civil Engineering, Qazvin Branch, Islamic Azad University)
  • Received : 2019.06.19
  • Accepted : 2020.08.21
  • Published : 2021.01.25

Abstract

This paper aims to present a novelty damage detection method to identify damage locations by the simultaneous use of both the energy and displacement damage indices. Using this novelty method, the damaged location and even the damaged floor are accurately detected. As a first method, a combination of the instantaneous frequency energy index (EDI) and the structural acceleration responses are used. To evaluate the first method and also present a rapid assessment method, the Displacement Damage Index (DDI), which consists of the error reliability (β) and Normal Probability Density Function (NPDF) indices, are introduced. The innovation of this method is the simultaneous use of displacement-acceleration responses during one process, which is more effective in the rapid evaluation of damage patterns with velocity vectors. In order to evaluate the effectiveness of the proposed method, various damage scenarios of the ASCE benchmark problem, and the effects of measurement noise were studied numerically. Extensive analyses show that the rapid proposed method is capable of accurately detecting the location of sparse damages through the building. Finally, the proposed method was validated by experimental studies of a six-story steel building structure with single and multiple damage cases.

Keywords

References

  1. Afonso, V.X. and Tompkins, W.J. (1995), "Detecting ventricular fibrillation", IEEE Eng. Medicine Biology Mag., 14(2), 152-159. https://doi.org/ 10.1109/51.376752
  2. Barr, D.R. and Davidson, T. (1973), "A Kolmogorov-Smirnov test for censored samples", Technometrics, 15(4), 739-757. https://doi.org/10.1080/00401706.1973.10489108
  3. Bozyigit, B., Yesilce, Y. and Wahab, M.A. (2020), "Transfer matrix formulations and single variable shear deformation theory for crack detection in beam-like structures", Struct. Eng. Mech., 73(2), 109-121. https://doi.org/10.12989/sem.2020.73.2.109.
  4. Cantero, D. and Basu, B. (2015), "Railway infrastructure damage detection using wavelet transformed acceleration response of traversing vehicle", Struct. Control Health Monitor., 22(1), 62-70. https://doi.org/10.1002/stc.1660
  5. Cha, Y. J. and Wang, Z. (2018), "Unsupervised novelty detection-based structural damage localization using a density peaks-based fast clustering algorithm", Struct. Health Monitor., 17(2), 313-324. https://doi.org/10.1177/1475921717691260.
  6. Derksen, H. and Weyman, J. (2005), "Quiver represantations", Notices of the AMS, 52(2), 200-206.
  7. Dyke, S.J., Bernal, D., Beck, J.L. and Ventura, C. (2001), "An experimental benchmark problem in structural health monitoring", Proceedings of the 3rd International Workshop on Structural Health Monitoring, 488-497. CRC Press, Florida, USA.
  8. Ebrahimi, F. and Heidari, E. (2018), "Vibration characteristics of advanced nanoplates in humid-thermal environment incorporating surface elasticity effects via differential quadrature method", Struct. Eng. Mech., 68(1), 131-157. https://doi.org/10.12989/sem.2018.68.1.131
  9. Entezami, A., Shariatmadar, H. and Karamodin, A. (2019), "Data-driven damage diagnosis under environmental and operational variability by novel statistical pattern recognition methods", Struct. Health Monitor., 18(5-6), 1416-1443. https://doi.org/10.1177/1475921718800306.
  10. Ghasemi, S.H. and Nowak, A.S. (2017), "Target reliability for bridges with consideration of ultimate limit state", Eng. Struct., 152, 226-237. https://doi.org/10.1016/j.engstruct.2017.09.012
  11. Hera, A. and Hou, Z. (2004), "Application of wavelet approach for ASCE structural health monitoring benchmark studies", J. Eng. Mech., 130(1), 96-104. https://doi.org/10.1061/(ASCE)0733-9399(2004)130:1(96).
  12. Hou, Z. and Hera, A. (2002, June), "Progress of phase II study of the ASCE health monitoring benchmark data using wavelet approach", Proceedings of the 15th ASCE Engineering Mechanics Conference, Columbia University, New York, USA. 2-5.
  13. Hsu, T.Y. and Loh, C.H. (2013), "A frequency response function change method for damage localization and quantification in a shear building underground excitation", Earthq. Eng. Struct. Dynam., 42(5), 653-668. https://doi.org/10.1002/eqe.2235
  14. Huang, N.E. (2014), "Introduction to the Hilbert-Huang transform and its related mathematical problems", Hilbert-Huang Transform and its Applications, , World Scientific, Singapore. 1-26.
  15. Huang, N.E., Salvino, L.W., Nieh, Y.Y., Wang, G. and Chen, X. (2013), "HHT-based structural health monitoring", Health Assessment of Engineered Structures: Bridges, Buildings and Other Infrastructures, World Scientific, Singapore. 203-240. https://doi.org/10.1142/9789814439022_0008
  16. Huo, L.S., Li, X., Yang, Y.B. and Li, H.N. (2016), "Damage detection of structures for ambient loading based on cross correlation function amplitude and SVM", Shock Vib., 2016, https://doi.org/10.1155/2016/3989743.
  17. Huston, D. (2010), Structural Sensing, Health Monitoring and Performance Evaluation, CRC Press, Florida, USA.
  18. Ji, J., Qu, J., Chai, Y., Zhou, Y., Tang, Q. and Ren, H. (2018), "An algorithm for sensor fault diagnosis with EEMD-SVM", Transactions of the Institute of Measurement and Control, 40(6), 1746-1756. https://doi.org/10.1177%2F0142331217690579. https://doi.org/10.1177%2F0142331217690579
  19. Johnson, E.A., Lam, H.F., Katafygiotis, L.S. and Beck, J.L. (2004), "Phase I IASC-ASCE structural health monitoring benchmark problem using simulated data", J. Eng. Mech., 130(1), 3-15. https://doi.org/10.1061/(ASCE)0733-9399(2004)130:1(3)
  20. Johnson, E., Lam, H.F., Katafygiotis, L.S. and Beck, J.L. (2001), "A benchmark problem for structural health monitoring and damage detection", Struct. Control Civil Infrastruct. Eng., 317-324. https://doi.org/10.1142/9789812811707_0028.
  21. Khosraviani, M. J. and Ghasemi, M. (2016, November), "Damage localization in beam-like structure under moving load by Empirical Mode Decomposition", Life-Cycle of Engineering Systems: Emphasis on Sustainable Civil Infrastructure: Proceedings of the Fifth International Symposium on Life-Cycle Civil Engineering (IALCCE 2016), 291. Delft, The Netherlands, October.
  22. Kourehli, S.S. (2017), "Damage Diagnosis of Structures Using Modal Data and Static Response", Periodica Polytechnica Civil Eng., 61(1), 135-145. https://doi.org/10.3311/PPci.7646
  23. Kourehli, S.S. (2018), "Prediction of unmeasured mode shapes and structural damage detection using least squares support vector machine", Struct. Monitor. Maintenance, 5(3), 379-390. https://doi.org/10.12989/smm.2018.5.3.379.
  24. Kati, H.D. and Gokdag, H. (2018), "Vibration analysis of a Timoshenko beam carrying 3D tip mass by using differential transform method", Struct. Eng. Mech., 65(4), 381-388. http://dx.doi.org/10.12989/sem.2018.65.4.381.
  25. Lam, H.F., Katafygiotis, L.S. and Mickleborough, N.C. (2004), "Application of a statistical model updating approach on phase I of the IASC-ASCE structural health monitoring benchmark study", J. Eng. Mech., 130(1), 34-48. https://doi.org/10.1061/(ASCE)0733-9399(2004)130:1(34).
  26. Melhem, H. and Kim, H. (2003), "Damage detection in concrete by Fourier and wavelet analyses", J. Eng. Mech., 129(5), 571-577. https://doi.org/10.1061/(ASCE)0733-9399(2003)129:5(571).
  27. Nair, K.K., Kiremidjian, A.S. and Law, K.H. (2006), "Time series-based damage detection and localization algorithm with application to the ASCE benchmark structure", J. Sound Vib., 291(1-2), 349-368. https://doi.org/10.1016/j.jsv.2005.06.016.
  28. Nowak, A.S. and Collins, K.R. (2012), Reliability of Structures, CRC Press, Florida, USA.
  29. Onat, O. (2019), "Fundamental vibration frequency prediction of historical masonry bridge", Struct. Eng. Mech., 69(2), 155-162. https://doi.org/10.12989/sem.2019.69.2.155.
  30. Ogata, K. (1995), Discrete-time Control Systems, Vol. 2, Prentice Hall, Englewood Cliffs, NJ, USA.
  31. Papoulis, A. (1977), Signal Analysis, Vol. 191, McGraw-Hill, NY, USA.
  32. Pierdicca, A., Clementi, F., Maracci, D., Isidori, D. and Lenci, S. (2016), "Damage detection in a precast structure subjected to an earthquake: A numerical approach", Eng. Struct., 127, 447-458. https://doi.org/10.1016/j.engstruct.2016.08.058.
  33. Piombo, B.A.D., Fasana, A., Marchesiello, S. and Ruzzene, M. (2000), "Modelling and identification of the dynamic response of a supported bridge", Mech. Syst. Signanl Process., 14(1), 75-89. https://doi.org/10.1006/mssp.1999.1266.
  34. Proakis, J.G. and Manolakis, D.G. (1996), Digital Signal Processing, Vol. 3, Prentice Hall, NJ, USA.
  35. Rafiei, M.H., Khushefati, W.H., Demirboga, R. and Adeli, H. (2017), "Supervised deep restricted Boltzmann machine for estimation of concrete," ACI Mater. J., 114(2), 237-244.
  36. Sifuzzaman, M., Islam, M.R. and Ali, M.Z. (2009), "Application of wavelet transform and its advantages compared to Fourier transform", J. Physical Sci., 13, 121-134. http://inet.vidyasagar.ac.in:8080/jspui/handle/123456789/779.
  37. Sohn, H., Farrar, C. R., Hemez, F. M. and Czarnecki, J. J. (2002), "A Review of Structural Health Review of Structural Health Monitoring Literature 1996-2001", No. LA-UR-02-2095, Los Alamos National Laboratory; USA.
  38. Tang, J.P., Chiou, D.J., Chen, C.W., Chiang, W.L., Hsu, W.K., Chen, C.Y. and Liu, T.Y. (2011), "RETRACTED: A case study of damage detection in benchmark buildings using a Hilbert-Huang Transform-based method", J. Vib. Control, 17(4), 623-636. https://doi.org/10.117/1077546309360053
  39. Than Soe, M. (2013), "Vibration-based finite element model updating and structural damage identification", Ph.D. Dissertation, University of Greenwich, London, United Kingdom.
  40. Wang, Z. and Cha, Y.J. (2020), "Unsupervised deep learning approach using a deep auto-encoder with an one-class support vector machine to detect structural damage," Struct. Health Monitor., July, https://doi.org/10.1177/1475921720934051.
  41. WenQin, H., Ying, L., AiJun, G. and Yuan, F.G. (2016), "Damage modes recognition and hilbert-huang transform analyses of CFRP laminates utilizing acoustic emission technique", Appl. Compos. Mater., 23(2), 155-178. https://doi.org/10.1007/s10443-015-9454-3.
  42. Wu, J.R. and Li, Q.S. (2006), "Structural parameter identification and damage detection for a steel structure using a two-stage finite element model updating method", J. Construct. Steel Res., 62(3), 231-239. https://doi.org/10.1016/j.jcsr.2005.07.003.
  43. Yang, J.N., Lei, Y., Lin, S. and Huang, N. (2004), "Hilbert-Huang based approach for structural damage detection", J. Eng. Mech., 130(1), 85-95. https://doi.org/10.1061/(ASCE)0733-9399(2004)130:1(85).
  44. Yang, J.N., Lei, Y., Pan, S. and Huang, N. (2003), "System identification of linear structures based on Hilbert-Huang spectral analysis. Part 1: Normal modes", Earthq. Eng. Struct. Dynam., 32(9), 1443-1467. https://doi.org/10.1002/eqe.287.
  45. Song, Z., Li, W., He, X. and Xie, D. (2019), "Free vibration analysis of beams with various interfaces by using a modified matched interface and boundary method", Struct. Eng. Mech., 72(1), 1-17. https://doi.org/10.12989/sem.2019.72.1.001
  46. Zhang, Y., Lian, J. and Liu, F. (2016), "An improved filtering method based on EEMD and wavelet-threshold for modal parameter identification of hydraulic structure", Mech. Syst. Signanl Process., 68, 316-329. https://doi.org/10.1016/j.ymssp.2015.06.020.