Damage Detection of Structures Identified with Deterministic-Stochastic Models Using Seismic Data

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Abstract

A deterministic-stochastic subspace identification method is adopted and experimentally verified in this study to identify the equivalent single-input-multiple-output system parameters of the discrete-time state equation. The method of damage locating vector (DLV) is then considered for damage detection. A series of shaking table tests using a five-storey steel frame has been conducted. Both single and multiple damage conditions at various locations have been considered. In the system identification analysis, either full or partial observation conditions have been taken into account. It has been shown that the damaged stories can be identified from global responses of the structure to earthquakes if sufficiently observed. In addition to detecting damage(s) with respect to the intact structure, identification of new or extended damages of the as-damaged counterpart has also been studied. This study gives further insights into the scheme in terms of effectiveness, robustness, and limitation for damage localization of frame systems.

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Huang, M. C., Wang, Y. P., & Chang, M. L. (2014). Damage Detection of Structures Identified with Deterministic-Stochastic Models Using Seismic Data. Scientific World Journal, 2014. https://doi.org/10.1155/2014/879341

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