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Open AccessArticle

Structural Damage Identification Based on AR Model with Additive Noises Using an Improved TLS Solution

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School of Civil Engineering and Architecture, Wuhan University of Technology, Luoshi Road No.122, Wuhan 430070, China
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School of Safety Science and Emergency Management, Wuhan University of Technology, Luoshi Road No.122, Wuhan 430070, China
*
Author to whom correspondence should be addressed.
Sensors 2019, 19(19), 4341; https://doi.org/10.3390/s19194341
Received: 4 September 2019 / Revised: 4 October 2019 / Accepted: 7 October 2019 / Published: 8 October 2019
Structural damage is inevitable due to the structural aging and disastrous external excitation. The auto-regressive (AR) based method is one of the most widely used methods for structural damage identification. In this regard, the classical least-squares algorithm is often utilized to solve the AR model. However, this algorithm generally could not take all the observed noises into account. In this study, a partial errors-in-variables (EIV) model is used so that both the current and prior observation errors are considered. Accordingly, a total least-squares (TLSE) solution is introduced to solve the partial EIV model. The solution estimates and accounts for the correlations between the current observed data and the design matrix. An effective damage indicator is chosen to count for damage levels of the structures. Both mathematical and finite element simulation results show that the proposed TLSE method yields better accuracy than the classical LS method and the AR model. Finally, the response data of a high-rise building shaking table test is used for demonstrating the effectiveness of the proposed method in identifying the location and damage degree of a model structure. View Full-Text
Keywords: damage identification; auto-regressive model; total least-squares method damage identification; auto-regressive model; total least-squares method
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Wu, C.; Li, S.; Zhang, Y. Structural Damage Identification Based on AR Model with Additive Noises Using an Improved TLS Solution. Sensors 2019, 19, 4341.

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