Indirect bridge modal parameters identification with one stationary and one moving sensors and stochastic subspace identification

Li, J; Zhu, X; Law, SS; Samali, B

Indirect bridge modal parameters identification with one stationary and one moving sensors and stochastic subspace identification

Li, J

Zhu, X

Law, SS Samali, B

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Publication Type:: Journal Article
Citation:: Journal of Sound and Vibration, 2019, 446 pp. 1 - 21
Issue Date:: 2019-04-28

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Field	Value	Language
dc.contributor.author	Li, J https://orcid.org/0000-0001-9181-3653	en_US
dc.contributor.author	Zhu, X https://orcid.org/0000-0001-5083-9320	en_US
dc.contributor.author	Law, SS	en_US
dc.contributor.author	Samali, B https://orcid.org/0000-0002-3426-7745	en_US
dc.date.available	2021-01-17T18:03:34Z
dc.date.issued	2019-04-28	en_US
dc.identifier.citation	Journal of Sound and Vibration, 2019, 446 pp. 1 - 21	en_US
dc.identifier.issn	0022-460X	en_US
dc.identifier.uri	http://hdl.handle.net/10453/135524
dc.description.abstract	© 2019 Elsevier Ltd A new indirect strategy is proposed to estimate the bridge modal parameters from the dynamic responses of two vehicles using stochastic subspace identification technique. The effect of ambient excitation, such as ongoing traffic, is simulated as white-noise excitation at the bridge supports. The state-space model of the vehicle-bridge interaction system is derived for a single-degree-of-freedom quarter-car model and the bridge deck modeled as a simply-supported Euler-Bernoulli beam. Bridge modal frequencies can be estimated accurately from the vehicle responses. Two instrumented vehicles are required to estimate the bridge mode shapes, with one serving as a fixed reference sensor and the other as a moving sensor. The measured accelerations from the vehicles are divided into segments and each pair of signal segments forms a state-space identification problem. Local mode shape value from each signal segment can be estimated using the reference-based SSI method. A rescaling on the local mode shape values is applied to construct the global mode shapes. Effects of the bridge surface roughness, measurement noise and vehicle properties on the mode shape identification are also numerically studied. A vehicle-bridge interaction model in the laboratory serves for the experimental validation of the proposed strategy. Both numerical and experimental results show that the proposed method can estimate the bridge modal parameters with acceptable accuracy.	en_US
dc.relation	http://purl.org/au-research/grants/arc/DP160103197
dc.relation.ispartof	Journal of Sound and Vibration	en_US
dc.relation.isbasedon	10.1016/j.jsv.2019.01.024	en_US
dc.rights	info:eu-repo/semantics/openAccess
dc.subject.classification	Acoustics	en_US
dc.title	Indirect bridge modal parameters identification with one stationary and one moving sensors and stochastic subspace identification	en_US
dc.type	Journal Article
utslib.citation.volume	446	en_US
utslib.for	0905 Civil Engineering	en_US
utslib.for	02 Physical Sciences	en_US
utslib.for	09 Engineering	en_US
pubs.embargo.period	Not known	en_US
pubs.organisational-group	/University of Technology Sydney
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
utslib.copyright.status	open_access	*
pubs.publication-status	Published	en_US
pubs.volume	446	en_US

Abstract:

© 2019 Elsevier Ltd A new indirect strategy is proposed to estimate the bridge modal parameters from the dynamic responses of two vehicles using stochastic subspace identification technique. The effect of ambient excitation, such as ongoing traffic, is simulated as white-noise excitation at the bridge supports. The state-space model of the vehicle-bridge interaction system is derived for a single-degree-of-freedom quarter-car model and the bridge deck modeled as a simply-supported Euler-Bernoulli beam. Bridge modal frequencies can be estimated accurately from the vehicle responses. Two instrumented vehicles are required to estimate the bridge mode shapes, with one serving as a fixed reference sensor and the other as a moving sensor. The measured accelerations from the vehicles are divided into segments and each pair of signal segments forms a state-space identification problem. Local mode shape value from each signal segment can be estimated using the reference-based SSI method. A rescaling on the local mode shape values is applied to construct the global mode shapes. Effects of the bridge surface roughness, measurement noise and vehicle properties on the mode shape identification are also numerically studied. A vehicle-bridge interaction model in the laboratory serves for the experimental validation of the proposed strategy. Both numerical and experimental results show that the proposed method can estimate the bridge modal parameters with acceptable accuracy.

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http://hdl.handle.net/10453/135524