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Thermal strain extraction methodologies for bridge structural condition assessment
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Zhu, Yanjie, Ni, Yi-Qing, Jesus, André H., Liu, Jingliang and Laory, Irwanda (2018) Thermal strain extraction methodologies for bridge structural condition assessment. Smart Materials and Structures, 27 (10). 105051. doi:10.1088/1361-665X/aad5fb ISSN 0964-1726.
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WRAP-thermal-strain-extraction-methodologies-bridge-structural-condition-assessment-Zhu-2018.pdf - Published Version - Requires a PDF viewer. Available under License Creative Commons Attribution Non-commercial No Derivatives 4.0. Download (2367Kb) | Preview |
Official URL: http://dx.doi.org/10.1088/1361-665X/aad5fb
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: | Journal Article | |||||||||
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| Subjects: | Q Science > QA Mathematics T Technology > TG Bridge engineering |
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| Divisions: | Faculty of Science, Engineering and Medicine > Engineering > Engineering | |||||||||
| Library of Congress Subject Headings (LCSH): | Truss bridges -- Research, Principal components analysis | |||||||||
| Journal or Publication Title: | Smart Materials and Structures | |||||||||
| Publisher: | Institute of Physics Publishing Ltd | |||||||||
| ISSN: | 0964-1726 | |||||||||
| Official Date: | 21 September 2018 | |||||||||
| Dates: |
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| Volume: | 27 | |||||||||
| Number: | 10 | |||||||||
| Article Number: | 105051 | |||||||||
| DOI: | 10.1088/1361-665X/aad5fb | |||||||||
| Status: | Peer Reviewed | |||||||||
| Publication Status: | Published | |||||||||
| Access rights to Published version: | Restricted or Subscription Access | |||||||||
| Date of first compliant deposit: | 31 July 2018 | |||||||||
| Date of first compliant Open Access: | 26 July 2019 | |||||||||
| RIOXX Funder/Project Grant: |
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