Thermal strain extraction methodologies for bridge structural condition assessment

Zhu, Yanjie, Ni, Yi-Qing, Jesus, Andre ORCID: https://orcid.org/0000-0002-5194-3469, Liu, Jingliang and Laory, Irwanda (2018) Thermal strain extraction methodologies for bridge structural condition assessment. Smart Materials and Structures, 27 (10). ISSN 0964-1726

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Abstract

This paper presents a feature extraction method to uncover the temperature effects on bridge responses, which combines mode decomposition, data reduction and blind separation. For mode decomposition, empirical mode decomposition (EMD) and ensemble empirical mode decomposition (EEMD) have been selected, followed by principal component analysis (PCA) for data size compression. The independent component analysis (ICA) is then employed for blind separation. The unique feature of the proposed method is the blind separation, which means temperature-induced response can be extracted from the mixed structural responses, without any prior information of the loading conditions and structural physical models. This study further evaluates the effects of extracting temperature-induced response on damage detectability when using Moving Principal Component Analysis (MPCA). The numerical analysis of a truss bridge is first used to evaluate the proposed method for thermal feature extraction, followed by a real truss bridge test in the structural laboratory in University of Warwick. Results from the numerical case study show that the method enables the separation of temperature-induced response, and furthermore, the EEMD, in mode decomposition, has a positive influence on the blind separation than EMD, when combined with PCA and ICA. Finally, the real truss bridge test demonstrates that the feature extraction method can enhance the probability of MPCA to uncover the damage, as the MPCA fails without proposed method.

Item Type: Article
Identifier: 10.1088/1361-665X/aad5fb
Additional Information: © 2018 IOP Publishing Ltd. This is an author-created, un-copyedited version of an article accepted for publication in Smart Materials and Structures. IOP Publishing Ltd is not responsible for any errors or omissions in this version of the manuscript or any version derived from it. The definitive publisher authenticated version is available online at https://doi.org/10.1088/1361-665X/aad5fb
Subjects: Construction and engineering > Digital signal processing
Construction and engineering > Civil and structural engineering
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Depositing User: Andre Jesus
Date Deposited: 28 Nov 2018 14:46
Last Modified: 06 Feb 2024 15:58
URI: https://repository.uwl.ac.uk/id/eprint/5629

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