Smart Structures and Systems

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Overall damage identification of flag-shaped hysteresis systems under seismic excitation

  • Zhou, Cong (Department of Mechanical Engineering, University of Canterbury) ;
  • Chase, J. Geoffrey (Department of Mechanical Engineering, University of Canterbury) ;
  • Rodgers, Geoffrey W. (Department of Mechanical Engineering, University of Canterbury) ;
  • Xu, Chao (School of Astronautics, Northwestern Polytechnical University) ;
  • Tomlinson, Hamish (Department of Mechanical Engineering, University of Canterbury)
  • Received : 2014.04.13
  • Accepted : 2014.11.01
  • Published : 2015.07.25
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Abstract

This research investigates the structural health monitoring of nonlinear structures after a major seismic event. It considers the identification of flag-shaped or pinched hysteresis behavior in response to structures as a more general case of a normal hysteresis curve without pinching. The method is based on the overall least squares methods and the log likelihood ratio test. In particular, the structural response is divided into different loading and unloading sub-half cycles. The overall least squares analysis is first implemented to obtain the minimum residual mean square estimates of structural parameters for each sub-half cycle with the number of segments assumed. The log likelihood ratio test is used to assess the likelihood of these nonlinear segments being true representations in the presence of noise and model error. The resulting regression coefficients for identified segmented regression models are finally used to obtain stiffness, yielding deformation and energy dissipation parameters. The performance of the method is illustrated using a single degree of freedom system and a suite of 20 earthquake records. RMS noise of 5%, 10%, 15% and 20% is added to the response data to assess the robustness of the identification routine. The proposed method is computationally efficient and accurate in identifying the damage parameters within 10% average of the known values even with 20% added noise. The method requires no user input and could thus be automated and performed in real-time for each sub-half cycle, with results available effectively immediately after an event as well as during an event, if required.

Keywords

Acknowledgement

Supported by : China Scholarship Council, University of Canterbury

References

  1. Alam, M.S., Youssef, M. and Nehdi, M. (2009), "Seismic performance of concrete frame structures reinforced with superelastic shape memory alloys", Smart Struct. Syst., 5(5), 565-585. https://doi.org/10.12989/sss.2009.5.5.565
  2. Atkinson, G.M. and Pierre, J.R. (2004), "Ground-motion response spectra in eastern North America for different critical damping values", Seismol. Res. Lett., 75(4), 541-545. https://doi.org/10.1785/gssrl.75.4.541
  3. Attanasi, G., Auricchio, F. and Fenves, G.L. (2009), "Feasibility assessment of an innovative isolation bearing system with shape memory alloys", J. Earthq. Eng., 13(1), 18-39. https://doi.org/10.1080/13632460902813216
  4. Bartera, F. and Giacchetti, R. (2004), "Steel dissipating braces for upgrading existing building frames", J. Constr. Steel Res., 60(3), 751-769. https://doi.org/10.1016/S0143-974X(03)00141-X
  5. Bernal, D. (2002), "Load vectors for damage localization", J. Eng. Mech.- ASCE, 128(1), 7-14. https://doi.org/10.1061/(ASCE)0733-9399(2002)128:1(7)
  6. Bernal, D. and Gunes, B. (2004), "Flexibility based approach for damage characterization: benchmark application", J. Eng. Mech.- ASCE, 130(1), 61-70. https://doi.org/10.1061/(ASCE)0733-9399(2004)130:1(61)
  7. Bernal, D. and Gunes, B. (2000), "Observer/Kalman and subspace identification of the UBC benchmark structural model", Proceedings of the 14th ASCE Engineering Mechanics Conference, Texas, May 21-24.
  8. Casciati, F. and Fuggini, C. (2011), "Monitoring a steel building using GPS sensors", Smart Struct. Syst., 7(5), 349 - 363. https://doi.org/10.12989/sss.2011.7.5.349
  9. Casciati, S. and Hamdaoui, K. (2008), "Experimental and numerical studies toward the implementation of shape memory alloy ties in masonry structures", Smart Struct. Syst., 4(2), 153-169. https://doi.org/10.12989/sss.2008.4.2.153
  10. Chang, P.C., Flatau, A. and Liu, S. (2003), "Review paper: health monitoring of civil infrastructure", Struct. Health Monit., 2(3), 257-267. https://doi.org/10.1177/1475921703036169
  11. Chase, J.G., Leo Hwang, K., Barroso, L. and Mander, J. (2005a), "A simple LMS-based approach to the structural health monitoring benchmark problem", Earthq. Eng. Struct. D., 34(6), 575-594. https://doi.org/10.1002/eqe.433
  12. Chase, J.G., Spieth, H.A., Blome, C.F. and Mander, J. (2005b), "LMS-based structural health monitoring of a non-linear rocking structure", Earthq. Eng. Struct. D., 34(8), 909-930. https://doi.org/10.1002/eqe.460
  13. Chopra, A.K. (2001), Dynamics of Structures: Theory and Applications to Earthquake Engineering, Prentice Hall, Englewood Cliffs, New Jersey, USA.
  14. Christopoulos, C., Filiatrault, A. and Folz, B. (2002), "Seismic response of self-centring hysteretic SDOF systems", Earthq. Eng. Struct. D., 31(5), 1131-1150. https://doi.org/10.1002/eqe.152
  15. Christopoulos, C., Filiatrault, A., Uang, C.M. and Folz, B. (2002), "Posttensioned energy dissipating connections for moment-resisting steel frames", J. Struct. Eng.- ASCE, 128(9), 1111-1120. https://doi.org/10.1061/(ASCE)0733-9445(2002)128:9(1111)
  16. Christopoulos, C., Tremblay, R., Kim, H.J. and Lacerte, M. (2008), "Self-centering energy dissipative bracing system for the seismic resistance of structures: development and validation", J. Struct. Eng.- ASCE, 134(1), 96-107. https://doi.org/10.1061/(ASCE)0733-9445(2008)134:1(96)
  17. Doebling, S.W., Farrar, C.R., Prime, M.B. and Shevitz, D.W. (1996), Damage Identification and Health Monitoring of Structural and Mechanical Systems from Changes in Their Vibration Characteristics: a Literature Review, Los Alamos National Lab, New Mexico, USA.
  18. Feder, P.I. (1975), "The log likelihood ratio in segmented regression", The Annals of Statistics, 3(1), 84-97. https://doi.org/10.1214/aos/1176343000
  19. Fu, G. and Moosa, A.G. (2002), "An optical approach to structural displacement measurement and its application", J. Eng. Mech.- ASCE, 128(5), 511-520. https://doi.org/10.1061/(ASCE)0733-9399(2002)128:5(511)
  20. Garlock, M.M., Ricles, J.M. and Sause, R. (2005), "Experimental studies of full-scale posttensioned steel connections", J. Struct. Eng.- ASCE, 131(3), 438-448. https://doi.org/10.1061/(ASCE)0733-9445(2005)131:3(438)
  21. Giraldo, D., Yoshida, O., Dyke, S.J. and Giacosa, L. (2004), "Control-oriented system identification using ERA", Struct. Control Health Monit., 11(4), 311-326. https://doi.org/10.1002/stc.46
  22. Hann, C.E., Singh-Levett, I., Deam, B.L., Mander, J.B. and Chase, J.G. (2009), "Real-time system identification of a nonlinear four-story steel frame structure-application to structural health monitoring", Sensors J. IEEE, 9(11), 1339-1346.
  23. Hudson, D.J. (1966), "Fitting segmented curves whose join points have to be estimated", J. Amer. Stat. Assoc., 61(316), 1097-1129. https://doi.org/10.1080/01621459.1966.10482198
  24. Hwang, J., Yun, H., Park, S.K., Lee, D. and Hong, S. (2012),"Optimal methods of RTK-GPS/Accelerometer integration to monitor the displacement of structures", Sensors, 12(1), 1014-1034. https://doi.org/10.3390/s120101014
  25. International Conference of Building Officials (1997), Uniform Building Code, Whittier,CA,USA.
  26. Iwan, W.D. (2002), "R-SHAPE: a real-time structural health and performance evaluation system", Proceedings of the US Europe Workshop on Sensors and Smart Structures Technology, Lombardo, January.
  27. Iwan, W.D., Radulescu, D.C. and Radulescu, C. (2013), Extreme event performance evaluation using real-time hysteresis monitoring, US Patent 8,538,734.
  28. Koo, K.Y., Lee, J.J., Yun, C.B. and Kim, J.T. (2008), "Damage detection in beam-like structures using deflections obtained by modal flexibility matrices", Smart Struct. Syst., 4(5), 605-628. https://doi.org/10.12989/sss.2008.4.5.605
  29. Lee, K.J. and Yun, C.B. (2008), "Parameter identification for nonlinear behavior of RC bridge piers using sequential modified extended Kalman filter", Smart Struct. Syst., 4(3), 319-342. https://doi.org/10.12989/sss.2008.4.3.319
  30. 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)
  31. Lus, H., Betti, R., Yu, J. and De Angelis, M. (2003), "Investigation of a system identification methodology in the context of the ASCE benchmark problem", J. Eng. Mech.- ASCE, 130(1), 71-84.
  32. Nayyerloo, M., Chase, J., MacRae, G. and Chen, X. (2011), "LMS-based approach to structural health monitoring of nonlinear hysteretic structures", Struct. Health Monit., 10(4), 429-444. https://doi.org/10.1177/1475921710379519
  33. Ozbulut, O.E. and Hurlebaus, S. (2011), "Seismic assessment of bridge structures isolated by a shape memory alloy/rubber-based isolation system", SmMaS, 20(1), 015003.
  34. PEER. (2005), http://peer.berkeley.edu/smcat.
  35. Pekcan, G., Mander, J.B. and Chen, S.S. (1999), "Fundamental considerations for the design of non-linear viscous dampers", Earthq. Eng. Struct. D., 28(11), 1405-1425. https://doi.org/10.1002/(SICI)1096-9845(199911)28:11<1405::AID-EQE875>3.0.CO;2-A
  36. Powell, G.H. and Allahabadi, R. (1988), "Seismic damage prediction by deterministic methods: concepts and procedures", Earthq. Eng. Struct. D., 16(5), 719-734. https://doi.org/10.1002/eqe.4290160507
  37. Psimoulis, P.A. and Stiros, S.C. (2008), "Experimental assessment of the accuracy of GPS and RTS for the determination of the parameters of oscillation of major structures", CACAIE, 23(5), 389-403.
  38. Quandt, R.E. (1958), "The estimation of the parameters of a linear regression system obeying two separate regimes", J. Amer. Statist. Assoc., 53(284), 873-880. https://doi.org/10.1080/01621459.1958.10501484
  39. Ricles, J.M., Sause, R., Garlock, M.M. and Zhao, C. (2001), "Posttensioned seismic-resistant connections for steel frames", J. Struct. Eng.- ASCE, 127(2), 113-121. https://doi.org/10.1061/(ASCE)0733-9445(2001)127:2(113)
  40. Rodgers, G.W., Solberg, K.M., Chase, J.G., Mander, J.B., Bradley, B.A., Dhakal, R.P. and Li, L. (2008), "Performance of a damage-protected beam-column subassembly utilizing external HF2V energy dissipation devices", Earthq. Eng. Struct. D., 37(13), 1549-1564. https://doi.org/10.1002/eqe.830
  41. Safak, E. and Hudnut, K. (2006), "Real-time structural monitoring and damage detection by acceleration and GPS sensors", Proceedings of the 8th US National Conference on Earthquake Engineering, San Francisco, California, April 18-22.
  42. Sato, T. and Qi, K. (1998), "Adaptive $H{\infty}$ filter: its application to structural identification", J. Eng. Mech.- ASCE, 124(11), 1233-1240. https://doi.org/10.1061/(ASCE)0733-9399(1998)124:11(1233)
  43. Smyth, A. and Wu, M. (2007), "Multi-rate Kalman filtering for the data fusion of displacement and acceleration response measurements in dynamic system monitoring", MSSP, 21(2), 706-723.
  44. Teran-Gilmore, A., Avila, E. and Rangel, G. (2003), "On the use of plastic energy to establish strength requirements in ductile structures", Eng. Struct., 25(7), 965-980. https://doi.org/10.1016/S0141-0296(03)00040-3
  45. Teran-Gilmore, A. and Jirsa, J.O. (2005), "A damage model for practical seismic design that accounts for low cycle fatigue", Earthq. Spectra, 21(3), 803-832. https://doi.org/10.1193/1.1979500
  46. Tremblay, R., Lacerte, M. and Christopoulos, C. (2008), "Seismic response of multistory buildings with self-centering energy dissipative steel braces", J. Struct. Eng.- ASCE., 134(1), 108-120. https://doi.org/10.1061/(ASCE)0733-9445(2008)134:1(108)
  47. Walpole, R.E., Myers, R.H. and Myers, S.L. (2011), Probability and Statistics for Engineers and Scientists, Pearson Prentice Hall, Upper Saddle River.
  48. Xu, C., Chase, J.G. and Rodgers, G.W. (2014), "Physical parameter identification of nonlinear base-isolated buildings using seismic response data", Comput Struct., 145(1), 47-57. https://doi.org/10.1016/j.compstruc.2014.08.006
  49. Yan, G., Duan, Z. and Ou, J. (2009), "Damage detection for truss or frame structures using an axial strain flexibility", Smart Struct. Syst., 5(3), 291-316. https://doi.org/10.12989/sss.2009.5.3.291
  50. Yang, J.N., Lin, S., Huang, H. and Zhou, L. (2006), "An adaptive extended Kalman filter for structural damage identification", Struct. Control Health Monit., 13(4), 849-867. https://doi.org/10.1002/stc.84
  51. Zhou, C., Li, H.N., Li, D.S., Lin, Y.X. and Yi, T.H. (2013), "Online damage detection using pair cointegration method of time-varying displacement", Smart Struct. Syst., 12(3), 309-325. https://doi.org/10.12989/sss.2013.12.3_4.309

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