Abstract
Early structural damage identification to obtain an accurate condition assessment can assist in the reprioritization of structural retrofitting schedules in order to guarantee structural safety. Nowadays, seismic isolation technology has been applied in a wide variety of infrastructure, such as buildings, bridges, etc., and the health conditions of these nonlinear hysteretic vibration isolation systems have received considerable attention. To effectively detect structural damage in vibration isolation systems based on vibration data, three time-domain analysis techniques, referred to as the adaptive extended Kalman filter (AEKF), adaptive sequential nonlinear least-square estimation (ASNLSE) and adaptive quadratic sum-squares error (AQSSE), have been investigated. In this research, these analysis techniques are compared in terms of accuracy, convergence and efficiency, for structural damage detection using experimental data obtained through a series of laboratory tests based on a base-isolated structural model subjected to El Centro and Kobe earthquake excitations. The capability of the AEKF, ASNLSE and AQSSE approaches in tracking structural damage is demonstrated and compared.
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Supported by: National Natural Science Foundation of China under Grant No. 11172128; US National Science Foundation under Grant No. CMMI-0853395; the Funds for International Cooperation and Exchange of the National Natural Science Foundation of China under Grant No. 61161120323; the Jiangsu Foundation for Excellent Talent of China under Grant No. 2010-JZ-004; the Jiangsu Graduate Training Innovation Project under Grant No. CXLX11_0171
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Mu, T., Zhou, L. & Yang, J.N. Comparison of adaptive structural damage identification techniques in nonlinear hysteretic vibration isolation systems. Earthq. Eng. Eng. Vib. 12, 659–667 (2013). https://doi.org/10.1007/s11803-013-0204-y
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DOI: https://doi.org/10.1007/s11803-013-0204-y