Bridge Operational Modal Identification Using Sparse Blind Source Separation

Li, JT; Zhu, XQ; Samali, B

Bridge Operational Modal Identification Using Sparse Blind Source Separation

Li, JT Zhu, XQ Samali, B

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Publisher:: Springer
Publication Type:: Chapter
Citation:: ACMSM25, 2020, 37, pp. 911-920
Issue Date:: 2020-01-01

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Field	Value	Language
dc.contributor.author	Li, JT
dc.contributor.author	Zhu, XQ
dc.contributor.author	Samali, B
dc.contributor.editor	Wang, CM
dc.contributor.editor	Ho, JCM
dc.contributor.editor	Kitipornchai, S
dc.date.accessioned	2021-02-25T01:51:15Z
dc.date.available	2021-02-25T01:51:15Z
dc.date.issued	2020-01-01
dc.identifier.citation	ACMSM25, 2020, 37, pp. 911-920
dc.identifier.isbn	978-981-13-7602-3
dc.identifier.uri	http://hdl.handle.net/10453/146441
dc.description.abstract	© 2020, Springer Nature Singapore Pte Ltd. The bridge infrastructures are subjected to continuous degradation due to ageing, environmental and excess loading. Monitoring of these structures is a key part of any maintenance strategy as it can give early warning if a bridge is becoming unsafe. Most of the current approaches are using direct measurements that the sensors are installed at different specific locations on the bridge to capture the dynamic characteristics of the structure under random input, such as wind loads, traffic loads and ground motions. Based on the assumption on the white noise characteristics of the random input, structural properties of the bridge could be extracted from the vibration responses only. However, the bridge is subjected to non-stationary traffic loads, and the frequency characteristics of vibrations are varied. Especially for short-span bridges, the non-stationary traffic excitation is significant and most of the existing output-only structural identification methods could not be used to assess the bridge condition. This study proposes a blind source separation (BSS) method using short time Fourier transform (STFT) for the analysis of non-stationary measurements in time frequency (TF) domain. The proposed method is capable of source component separation from response measurement for underdetermined problems when the number of independent measurements (sensors) is less than that of source component. The proposed method is applied to a cable-stayed bridge in the field for the operational modal identification under different traffic conditions.
dc.format.extent	103
dc.language	en
dc.publisher	Springer
dc.relation	http://purl.org/au-research/grants/arc/DP160103197
dc.relation.ispartof	ACMSM25
dc.relation.ispartofseries	Lecture Notes in Civil Engineering
dc.relation.isbasedon	10.1007/978-981-13-7603-0_86
dc.rights	info:eu-repo/semantics/openAccess
dc.title	Bridge Operational Modal Identification Using Sparse Blind Source Separation
dc.type	Chapter
utslib.citation.volume	37
pubs.organisational-group	/University of Technology Sydney/Faculty of Engineering and Information Technology
pubs.organisational-group	/University of Technology Sydney/Faculty of Engineering and Information Technology/School of Civil and Environmental Engineering
pubs.organisational-group	/University of Technology Sydney
utslib.copyright.status	open_access	*
pubs.consider-herdc	false
dc.date.updated	2021-02-25T01:51:13Z
pubs.place-of-publication	Singapore
pubs.publication-status	Published
pubs.volume	37
dc.location	Singapore

Abstract:

© 2020, Springer Nature Singapore Pte Ltd. The bridge infrastructures are subjected to continuous degradation due to ageing, environmental and excess loading. Monitoring of these structures is a key part of any maintenance strategy as it can give early warning if a bridge is becoming unsafe. Most of the current approaches are using direct measurements that the sensors are installed at different specific locations on the bridge to capture the dynamic characteristics of the structure under random input, such as wind loads, traffic loads and ground motions. Based on the assumption on the white noise characteristics of the random input, structural properties of the bridge could be extracted from the vibration responses only. However, the bridge is subjected to non-stationary traffic loads, and the frequency characteristics of vibrations are varied. Especially for short-span bridges, the non-stationary traffic excitation is significant and most of the existing output-only structural identification methods could not be used to assess the bridge condition. This study proposes a blind source separation (BSS) method using short time Fourier transform (STFT) for the analysis of non-stationary measurements in time frequency (TF) domain. The proposed method is capable of source component separation from response measurement for underdetermined problems when the number of independent measurements (sensors) is less than that of source component. The proposed method is applied to a cable-stayed bridge in the field for the operational modal identification under different traffic conditions.

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http://hdl.handle.net/10453/146441