Smart Structures and Systems

  • 제6권9호
  • /
  • Pages.1057-1077
  • /
  • 2010
  • /
  • 1738-1584(pISSN)
  • /
  • 1738-1991(eISSN)
테크노프레스 (Techno-Press)
권호 표지
DOI QR코드

DOI QR Code

Comparison of various structural damage tracking techniques based on experimental data

  • Huang, Hongwei (State Key Laboratory for Disaster Reduction in Civil Engineering, Tongji University) ;
  • Yang, Jann N. (Department of Civil and Environmental Engineering, University of California) ;
  • Zhou, Li (College of Aerospace Engineering, Nanjing University of Aeronautics and Astronautics)
  • 투고 : 2009.07.28
  • 심사 : 2010.06.16
  • 발행 : 2010.12.25
⟨ 이전 논문 다음 논문 ⟩

초록

An early detection of structural damages is critical for the decision making of repair and replacement maintenance in order to guarantee a specified structural reliability. Consequently, the structural damage detection, based on vibration data measured from the structural health monitoring (SHM) system, has received considerable attention recently. The traditional time-domain analysis techniques, such as the least square estimation (LSE) method and the extended Kalman filter (EKF) approach, require that all the external excitations (inputs) be available, which may not be the case for some SHM systems. Recently, these two approaches have been extended to cover the general case where some of the external excitations (inputs) are not measured, referred to as the adaptive LSE with unknown inputs (ALSE-UI) and the adaptive EKF with unknown inputs (AEKF-UI). Also, new analysis methods, referred to as the adaptive sequential non-linear least-square estimation with unknown inputs and unknown outputs (ASNLSE-UI-UO) and the adaptive quadratic sum-squares error with unknown inputs (AQSSE-UI), have been proposed for the damage tracking of structures when some of the acceleration responses are not measured and the external excitations are not available. In this paper, these newly proposed analysis methods will be compared in terms of accuracy, convergence and efficiency, for damage identification of structures based on experimental data obtained through a series of laboratory tests using a scaled 3-story building model with white noise excitations. The capability of the ALSE-UI, AEKF-UI, ASNLSE-UI-UO and AQSSE-UI approaches in tracking the structural damages will be demonstrated and compared.

키워드

참고문헌

  1. Alvin, K.F., Robertson, A.N., Reich, G.W. and Park, K.C. (2003), "Structural system identification: from reality to models", Comput. Struct., 81(12), 1149-1176. https://doi.org/10.1016/S0045-7949(03)00034-8
  2. Bernal, D. and Beck, J. (Ed.) (2004), "Preface to the special issue on phase I of the IASC-ASCE structural health monitoring benchmark", J. Eng. Mech.-ASCE, 130(1), 1-2. https://doi.org/10.1061/(ASCE)0733-9399(2004)130:1(1)
  3. Chang, F.K. (Ed.) (2005), "Structural Health Monitoring", Proceedings of the 5th International Workshop on Structural Health Monitoring, Stanford University, Stanford, CA, USA, September.
  4. Doebling, S.W., Farrar, C.R. and Prime, M.B. (1998), "A summary review of vibration-based damage identification methods", Shock Vib. Digest, 30(2), 91-105. https://doi.org/10.1177/058310249803000201
  5. Goodwin, G.C. and Sin, K.S. (1984), Adaptive Filtering, Prediction and Control, Prentice-Hall, Englewood, Cliffs, NJ, USA.
  6. Hoshiya, M. and Saito, E. (1984), "Structural identification by extended Kalman filter", J. Eng. Mech.-ASCE, 110(12), 1757-1770. https://doi.org/10.1061/(ASCE)0733-9399(1984)110:12(1757)
  7. Huang, H.W. (2006), System Identification and Damage Detection of Structures, PhD dissertation, Depatement of Civil and Environental Engineering, University of California, Irvine, CA, USA.
  8. Huang, H.W., Yang, J.N. and Zhou, L. (2010), "Adaptive quadratic sum-squares error with unknown inputs for structural damage identification", Struct. Control Health Monit., 17(4), 404-426.
  9. Lin, J.W., Betti, R., Smyth, A.W. and Longman, R.W. (2001), "On-line identification of non-linear hysteretic structural systems using a variable trace approach", Earthq. Eng. Struct. D., 30(9), 1279-1303. https://doi.org/10.1002/eqe.63
  10. Loh, C.H., Lin, C.Y. and Huang, C.C. (2000), "Time domain identification of frames under earthquake loadings", J. Eng. Mech.-ASCE, 126(7), 693-703. https://doi.org/10.1061/(ASCE)0733-9399(2000)126:7(693)
  11. Sato, T., Honda, R. and Sakanoue, T. (2001), "Application of adaptive Kalman filter to identify a five story frame structure using NCREE experimental data", Proceedings of 8th International Conference on Structural Safety and Reliability (ICOSSAR 2001), Newport Beach, CA, USA, June.
  12. Smyth, A.W., Masri, S.F., Kosmatopoulos, E.B., Chassiakos, A.G. and Caughey, T.K. (2002), "Development of adaptive modeling techniques for non-linear hysteretic systems", Int. J. Nonlinear Mech., 37(8), 1435-1451. https://doi.org/10.1016/S0020-7462(02)00031-8
  13. Wang, D. and Haldar, A. (1994), "Element-level system identification with unkown input", J. Eng. Mech.-ASCE, 120(1), 159-176. https://doi.org/10.1061/(ASCE)0733-9399(1994)120:1(159)
  14. Wang, D. and Haldar, A. (1997), "System identification with limited observations and without input", J. Eng. Mech.-ASCE, 123(5), 504-511. https://doi.org/10.1061/(ASCE)0733-9399(1997)123:5(504)
  15. Yang, J.N., Kim, J.H. and Agrawal, A.K. (2000), "Resetting semiactive stiffness damper for seismic response control", J. Struct. Eng.-ASCE, 126(12), 1427-1433. https://doi.org/10.1061/(ASCE)0733-9445(2000)126:12(1427)
  16. Yang, J.N. and Lin, S.L. (2004), "On-line identification of nonlinear hysteretic structures using an adaptive tracking technique", Int. J. Nonlinear Mech., 39(9), 1481-1491. https://doi.org/10.1016/j.ijnonlinmec.2004.02.010
  17. Yang, J.N. and Lin, S.L. (2005), "Identification of parametric variations of structures based on least squares estimation and adaptive tracking technique", J. Eng. Mech.-ASCE, 131(3), 290-298. https://doi.org/10.1061/(ASCE)0733-9399(2005)131:3(290)
  18. Yang, J.N., Lin, S.L., Huang, H.W. and Zhou, L. (2006a), "An adaptive extended Kalman filter for structural damage identification", Struct. Control Health Monit., 13(4), 849-867. https://doi.org/10.1002/stc.84
  19. Yang, J.N., Huang, H.W. and Lin, S.L. (2006b), "Sequential non-linear least-square estimation for damage identification of structures", Int. J. Nonlinear Mech., 41(1), 124-140. https://doi.org/10.1016/j.ijnonlinmec.2005.06.006
  20. Yang, J.N., Pan, S.W. and Lin, S.L. (2007a), "Least-squares estimation with unknown excitations for damage identification of structures", J. Eng. Mech.-ASCE, 133(1), 12-21. https://doi.org/10.1061/(ASCE)0733-9399(2007)133:1(12)
  21. Yang, J.N., Pan, S.W. and Huang, H.W. (2007b), "An adaptive extended Kalman filter for structural damage identifications II: unknown inputs", Struct. Control Health Monit., 14(3), 497-521. https://doi.org/10.1002/stc.171
  22. Yang, J.N., Bobrow, J., Jabbari, F., Leavitt, J., Cheng, C.P. and Lin, P.Y. (2007c), "Full-scale experimental verification of resetable semi-active stiffness dampers", Earthq. Eng. Struct. D., 36(9), 1255-1273. https://doi.org/10.1002/eqe.681
  23. Yang, J.N. and Huang, H.W. (2007), "Sequential non-linear least square estimation for damage identification of structures with unknown inputs and unknown outputs", Int. J. Nonlinear Mech., 42(5), 789-801. https://doi.org/10.1016/j.ijnonlinmec.2007.03.004
  24. Yang, J.N., Huang, H.W. and Pan, S.W. (2009), "Adaptive quadratic sum-squares error for structural damage identification", J. Eng. Mech.-ASCE, 135(2), 67-77. https://doi.org/10.1061/(ASCE)0733-9399(2009)135:2(67)
  25. Zhou, L., Wu, S.Y. and Yang, J.N. (2008), "Experimental study of an adaptive extended Kalman filter for structural damage identification", J. Infrastruct. Syst., 14(1), 42-51. https://doi.org/10.1061/(ASCE)1076-0342(2008)14:1(42)

피인용 문헌

  1. Information fusion diagnosis and early-warning method for monitoring the long-term service safety of high dams vol.13, pp.9, 2012, https://doi.org/10.1631/jzus.A1200122
  2. Data fusion based improved Kalman filter with unknown inputs and without collocated acceleration measurements vol.18, pp.3, 2016, https://doi.org/10.12989/sss.2016.18.3.375
  3. Damage assessment by stiffness identification for a full-scale three-story steel moment resisting frame building subjected to a sequence of earthquake excitations vol.15, pp.12, 2017, https://doi.org/10.1007/s10518-017-0190-y
  4. A Computationally Efficient Algorithm for Real-Time Tracking the Abrupt Stiffness Degradations of Structural Elements vol.31, pp.6, 2016, https://doi.org/10.1111/mice.12217
  5. The Stretching Method for Vibration-Based Structural Health Monitoring of Civil Structures vol.32, pp.4, 2017, https://doi.org/10.1111/mice.12255
  6. Automated structural dynamic modelling using model-free health monitoring results vol.53, pp.4, 2010, https://doi.org/10.5459/bnzsee.53.4.189-202