Abstract
To identify the model structure parameters in shaking table tests from seismic response, especially from time-varying response records, this paper presents a new methodology by combining the online recursive Adaptive Forgetting through Multiple Models (AFMM) and offline Auto-Regression with eXogenous variables (ARX) model. First, the AFMM is employed to detect whether the response of model structure is time-invariant or time-varying when subjected to strong motions. Second, if the response is time-invariant, the modal parameters are identified from the entire response record, such as the acceleration time-history using the ARX model. If the response is time-varying, the acceleration record is divided into three segments according to the accurate time-varying points detected by AFMM, and parameters are identified by only using the tail segment data, which is time-invariant and suited for analysis by the ARX model. Finally, the changes in dynamic properties due to various strong motions are obtained using the presented methodology. The feasibility and advantages of the method are demonstrated by identifying the modal parameters of a 12-story reinforced concrete (RC) frame structure in a shaking table test.
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References
Andersson P (1985), “Adaptive Forgetting in Recursive Identification through Multiple Models,” International Journal of Control, 42(5): 1175–1193.
China Academy of Building Research (1997), Specification of Testing Methods for Earthquake Resistant Building (J GJ 101-96), Beijing: China Architecture & Building Press.
Gong MS, Kashima T (2009), “Damage Detection of Reinforced Concrete Structure based on Limited Strong Motion Records,” Bulletin of the international Institute of Seismology and Earthquake Engineering, 43(1): 61–66.
Gong MS, Kashima T, Xie LL et al. (2010), “Structural Time-varying Modal Parameter Identification based on Its Strong Motion Records,” Journal of Vibration and Shock, 29(5): 171–175.
Hsu TY and Loh CH (2013), “A Frequency Response Function Change Method for Damage Localization and Quantification in a Shear Building under Ground Excitation,” Earthquake Engineering and Structural Dynamics, 42: 653–668.
Hu YC and Chen ZW (2008), “A Kind of Improved Discrete Orthogonal Polynomials in Fourier Domain for Experimental Modal Analysis,” Journal of Vibration Engineering, 21(1): 43–47.
Huang CS, Hung SL, Wen CM et al. (2003), “A Neural Network Approach for Structural Identification and Diagnosis of a Building from Seismic Response Data,” Earthquake Engineering and Structural Dynamics, 32(2): 187–206.
Lennart L (1999), System Identification-Theory for the User (2nd edition), PTR Prentice Hall, Upper Saddle River, NJ.
Lennart L (2013), System Identification Toolbox? -User’s Guide, The MathWorks, Inc.
Lin JW and Betti R (2004), “Online Identification and Damage Detection in Nonlinear Structural Systems Using a Variable Forgetting Factor Approach,” Earthquake Engineering and Structural Dynamics, 33(4): 419–444.
Lin RM (2011), “Development of a New and Effective Modal Identification Method-mathematical Formulations and Numerical Simulations,” Journal of Vibration and Control, 17(5): 741–758.
Loh CH and Lin HM (1996), “Application of Offline and Online Identification Techniques to Building Seismic Response Data,” Earthquake Engineering and Structural Dynamics, 25(3): 269–290.
Lu XL, Li PZ and Chen YQ (2003), Benchmark Test of a 12-story Reinforced Concrete Frame Model on Shaking Table, Study Report of State Key Laboratory for Disaster Reduction in Civil Engineering, Tongji University.
Rocco D, Marco M and Felice CP (2012), “Analysis of Non-stationary Structural Systems by Using a Bandvariable Filter,” Bulletin of Earthquake Engineering, 10: 895–911.
Shi YF and Chang CC (2012), “Substructural Timevarying Parameter Identification Using Wavelet Multiresolution Approximation,” Journal of Engineering Mechanics, 138(1): 50–59.
Yang YC and Satish N (2013), “Blind Modal Identification of Output-only Structures in Time-domain Based on Complexity Pursuit,” Ear thquake Engineering and Structural Dynamics, 42: 1885–1905.
Yi TH, Li HN and Wang GX (2006), “Structural Modal Parameter Identification Based on Wavelet Transform,” Journal of Vibration Engineering, 19(1): 51–56.
Yiannis H, Costas P and Maria P (2005), “Multi-objective Framework for Structural Model Identification,” Earthquake Engineering and Structural Dynamics, 34(6): 665–685.
Zhou Y and Lu XL (2012), Method and Technology for Shaking Table Model Test of Building Structures, Beijng: Science Press.
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Supported by: Basic Science & Research Foundation of IEM, CEA under Grant No. 2013B07; International Science & Technology Cooperation Program of China under Grant No. 2012DFA70810; Natural Science Foundation of China under Grant No. 50908216
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Gong, M., Sun, J. & Xie, L. Identification of model structure parameters via combination of AFMM and ARX from seismic response data. Earthq. Eng. Eng. Vib. 13, 411–423 (2014). https://doi.org/10.1007/s11803-014-0252-y
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DOI: https://doi.org/10.1007/s11803-014-0252-y