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Rapid post-earthquake damage assessment of ageing bridges using acceleration data

Rapid post-earthquake damage assessment of ageing bridges using acceleration data
Rapid post-earthquake damage assessment of ageing bridges using acceleration data

The role of signal-based nonlinear system identification methods for the rapid post-earthquake damage assessment of reinforced concrete (RC) bridge piers is explored. Experimental data from the shaking table tests of six RC columns with and without corrosion damage are used as benchmark data. The specimens are excited under three different ground motions with different time-series characteristics, structural detailing, and corrosion levels. The proposed system identification methods make use of accelerations alone (but not displacements as these are costly in-situ) to estimate the instantaneous frequency. The Wigner-Ville distribution and Hilbert transform are utilised due to their high resolution in both time and frequency domains. A combination of modal filtering and thresholding, using instantaneous amplitudes, are employed to attenuate the unreliable spikes in the Hilbert transform’s instantaneous frequency estimates. Their performance is benchmarked against a moving linear regression and standard white-noise tests. The comparison of the experimental results and time-frequency analysis indicates that the Wigner-Ville distribution and the Hilbert transform can produce reliable rapid damage detection when the response amplitude is large. The WignerVille distribution has better robustness and higher resolution. The robustness of the more computationally efficient Hilbert transform can be significantly improved by the introduction of modal filtering and thresholding.

International Association for Earthquake Engineering
Kashani, M. M.
d1074b3a-5853-4eb5-a4ef-7d741b1c025d
Alexander, N. A.
544fc8c7-40a4-4e81-aaab-89e78f1a6fc9
Ge, Xiao
3df78992-78e0-4c86-b10e-dcdaa53cacdb
Kashani, M. M.
d1074b3a-5853-4eb5-a4ef-7d741b1c025d
Alexander, N. A.
544fc8c7-40a4-4e81-aaab-89e78f1a6fc9
Ge, Xiao
3df78992-78e0-4c86-b10e-dcdaa53cacdb

Kashani, M. M., Alexander, N. A. and Ge, Xiao (2024) Rapid post-earthquake damage assessment of ageing bridges using acceleration data. In, 18th World Conference on Earthquake Engineering proceedings. International Association for Earthquake Engineering.

Record type: Book Section

Abstract

The role of signal-based nonlinear system identification methods for the rapid post-earthquake damage assessment of reinforced concrete (RC) bridge piers is explored. Experimental data from the shaking table tests of six RC columns with and without corrosion damage are used as benchmark data. The specimens are excited under three different ground motions with different time-series characteristics, structural detailing, and corrosion levels. The proposed system identification methods make use of accelerations alone (but not displacements as these are costly in-situ) to estimate the instantaneous frequency. The Wigner-Ville distribution and Hilbert transform are utilised due to their high resolution in both time and frequency domains. A combination of modal filtering and thresholding, using instantaneous amplitudes, are employed to attenuate the unreliable spikes in the Hilbert transform’s instantaneous frequency estimates. Their performance is benchmarked against a moving linear regression and standard white-noise tests. The comparison of the experimental results and time-frequency analysis indicates that the Wigner-Ville distribution and the Hilbert transform can produce reliable rapid damage detection when the response amplitude is large. The WignerVille distribution has better robustness and higher resolution. The robustness of the more computationally efficient Hilbert transform can be significantly improved by the introduction of modal filtering and thresholding.

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More information

Published date: 2024
Additional Information: Publisher Copyright: © 2024, International Association for Earthquake Engineering. All rights reserved.

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Local EPrints ID: 509627
URI: http://eprints.soton.ac.uk/id/eprint/509627
PURE UUID: c0389037-8bd2-4d5f-9105-6a721f6ad500
ORCID for M. M. Kashani: ORCID iD orcid.org/0000-0003-0008-0007
ORCID for Xiao Ge: ORCID iD orcid.org/0009-0007-0414-051X

Catalogue record

Date deposited: 26 Feb 2026 18:05
Last modified: 27 Feb 2026 02:52

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Contributors

Author: M. M. Kashani ORCID iD
Author: N. A. Alexander
Author: Xiao Ge ORCID iD

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