Bridge damage assessment under traffic and environmental variability: a case study on Yonghe cable-stayed bridge

Bridges are essential components of civil infrastructure that must operate safely and reliably. Traditional methods for assessing structural health rely on the concept that changes in a structure’s dynamic response may indicate potential damage. However, variations due to operational and environment...

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Autores: Zunino, Leonardo, Casas Rius, Joan Ramon|||0000-0003-4473-4308, Domaneschi, Marco
Tipo de recurso: artículo
Fecha de publicación:2025
País:España
Institución:Universitat Politècnica de Catalunya (UPC)
Repositorio:UPCommons. Portal del coneixement obert de la UPC
Idioma:inglés
OAI Identifier:oai:upcommons.upc.edu:2117/441622
Acceso en línea:https://hdl.handle.net/2117/441622
https://dx.doi.org/10.1016/j.engstruct.2025.120965
Access Level:acceso abierto
Palabra clave:Bridge damage detection
SHM
Variational mode decomposition
Hilbert-huang transform
Principal component analysis
K-means
Àrees temàtiques de la UPC::Enginyeria civil::Materials i estructures::Tipologies estructurals
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spelling Bridge damage assessment under traffic and environmental variability: a case study on Yonghe cable-stayed bridgeZunino, LeonardoCasas Rius, Joan Ramon|||0000-0003-4473-4308Domaneschi, MarcoBridge damage detectionSHMVariational mode decompositionHilbert-huang transformPrincipal component analysisK-meansÀrees temàtiques de la UPC::Enginyeria civil::Materials i estructures::Tipologies estructuralsBridges are essential components of civil infrastructure that must operate safely and reliably. Traditional methods for assessing structural health rely on the concept that changes in a structure’s dynamic response may indicate potential damage. However, variations due to operational and environmental factors (like traffic and temperature) can also contribute to these changes. This makes damage detection more challenging, as a bridge may still be safe while exhibiting changes in its dynamic response due to these factors. If these effects are not properly accounted for, it could lead to false positive alerts. This article proposes a methodology for detecting and localizing damage in bridges subjected to traffic loads and environmental variability. Acceleration signals from accelerometers placed on the deck of a cable-stayed bridge in China were analyzed as part of a real monitoring effort. This data bank enabled the implementation of the algorithm on real signals in both undamaged and damaged scenarios. Variational Mode Decomposition is used to decompose the signal into Intrinsic Mode Functions. The Hilbert Transform is then employed to extract instantaneous frequencies, which represent damage-sensitive features in this context. Furthermore, environmental effects are removed from the damage-sensitive features using Principal Component Analysis. Finally, damage detection and localization are achieved using a statistical analysis able to confirm the previous data processing. An unsupervised clustering algorithm (K-means) is used to detect changes between the undamaged state and the damaged one. The results demonstrate the method’s effectiveness when applied to real-world scenarios, suggesting its potential application in structural health monitoring.The authors would like to express their sincere gratitude to Prof. Hui Li, Harbin Institute of Technology, for providing the data and images of the actual damage conditions of the Yonghe Bridge. Funding: This work was supported by MIUR - PRIN 2022 ‘‘BIORESTORE – BIO-based Resilient Energy and Seismic retrofiT Of the REsidential building stock’’ [Prot. 202234HM8J, CUP E53C24002680006]; and by MCIN/AEI - ‘‘ERDF A way of making Europe’’ [Grant PID2021- 126405OB-C31]. This publication is also part of the project PNRRNGEU which has received funding from the MUR – DM 629/2024.Peer ReviewedElsevier20252025-11-0120252025-09-12journal articlehttp://purl.org/coar/resource_type/c_6501VoRhttp://purl.org/coar/version/c_970fb48d4fbd8a85info:eu-repo/semantics/articletext/htmlapplication/pdfhttps://hdl.handle.net/2117/441622https://dx.doi.org/10.1016/j.engstruct.2025.120965reponame:UPCommons. Portal del coneixement obert de la UPCinstname:Universitat Politècnica de Catalunya (UPC)InglésengAgencia Estatal de Investigación http://doi.org/10.13039/501100011033 Plan Estatal de Investigación Científica y Técnica y de Innovación 2021-2023 PID2021-126405OB-C31 DESARROLLO DE SENSORES MODULARES DE BAJO COSTE PARA SU USO EN IDENTIFICACION ESTRUCTURAL DE PUENTES SOMETIDOS A CARGAS QUASIESTATICASopen accesshttp://purl.org/coar/access_right/c_abf2Attribution-NonCommercial-NoDerivatives 4.0 Internationalhttp://creativecommons.org/licenses/by-nc-nd/4.0/info:eu-repo/semantics/openAccessoai:upcommons.upc.edu:2117/4416222026-05-27T15:37:01Z
dc.title.none.fl_str_mv Bridge damage assessment under traffic and environmental variability: a case study on Yonghe cable-stayed bridge
title Bridge damage assessment under traffic and environmental variability: a case study on Yonghe cable-stayed bridge
spellingShingle Bridge damage assessment under traffic and environmental variability: a case study on Yonghe cable-stayed bridge
Zunino, Leonardo
Bridge damage detection
SHM
Variational mode decomposition
Hilbert-huang transform
Principal component analysis
K-means
Àrees temàtiques de la UPC::Enginyeria civil::Materials i estructures::Tipologies estructurals
title_short Bridge damage assessment under traffic and environmental variability: a case study on Yonghe cable-stayed bridge
title_full Bridge damage assessment under traffic and environmental variability: a case study on Yonghe cable-stayed bridge
title_fullStr Bridge damage assessment under traffic and environmental variability: a case study on Yonghe cable-stayed bridge
title_full_unstemmed Bridge damage assessment under traffic and environmental variability: a case study on Yonghe cable-stayed bridge
title_sort Bridge damage assessment under traffic and environmental variability: a case study on Yonghe cable-stayed bridge
dc.creator.none.fl_str_mv Zunino, Leonardo
Casas Rius, Joan Ramon|||0000-0003-4473-4308
Domaneschi, Marco
author Zunino, Leonardo
author_facet Zunino, Leonardo
Casas Rius, Joan Ramon|||0000-0003-4473-4308
Domaneschi, Marco
author_role author
author2 Casas Rius, Joan Ramon|||0000-0003-4473-4308
Domaneschi, Marco
author2_role author
author
dc.subject.none.fl_str_mv Bridge damage detection
SHM
Variational mode decomposition
Hilbert-huang transform
Principal component analysis
K-means
Àrees temàtiques de la UPC::Enginyeria civil::Materials i estructures::Tipologies estructurals
topic Bridge damage detection
SHM
Variational mode decomposition
Hilbert-huang transform
Principal component analysis
K-means
Àrees temàtiques de la UPC::Enginyeria civil::Materials i estructures::Tipologies estructurals
description Bridges are essential components of civil infrastructure that must operate safely and reliably. Traditional methods for assessing structural health rely on the concept that changes in a structure’s dynamic response may indicate potential damage. However, variations due to operational and environmental factors (like traffic and temperature) can also contribute to these changes. This makes damage detection more challenging, as a bridge may still be safe while exhibiting changes in its dynamic response due to these factors. If these effects are not properly accounted for, it could lead to false positive alerts. This article proposes a methodology for detecting and localizing damage in bridges subjected to traffic loads and environmental variability. Acceleration signals from accelerometers placed on the deck of a cable-stayed bridge in China were analyzed as part of a real monitoring effort. This data bank enabled the implementation of the algorithm on real signals in both undamaged and damaged scenarios. Variational Mode Decomposition is used to decompose the signal into Intrinsic Mode Functions. The Hilbert Transform is then employed to extract instantaneous frequencies, which represent damage-sensitive features in this context. Furthermore, environmental effects are removed from the damage-sensitive features using Principal Component Analysis. Finally, damage detection and localization are achieved using a statistical analysis able to confirm the previous data processing. An unsupervised clustering algorithm (K-means) is used to detect changes between the undamaged state and the damaged one. The results demonstrate the method’s effectiveness when applied to real-world scenarios, suggesting its potential application in structural health monitoring.
publishDate 2025
dc.date.none.fl_str_mv 2025
2025-11-01
2025
2025-09-12
dc.type.none.fl_str_mv journal article
http://purl.org/coar/resource_type/c_6501
VoR
http://purl.org/coar/version/c_970fb48d4fbd8a85
dc.type.openaire.fl_str_mv info:eu-repo/semantics/article
format article
dc.identifier.none.fl_str_mv https://hdl.handle.net/2117/441622
https://dx.doi.org/10.1016/j.engstruct.2025.120965
url https://hdl.handle.net/2117/441622
https://dx.doi.org/10.1016/j.engstruct.2025.120965
dc.language.none.fl_str_mv Inglés
eng
language_invalid_str_mv Inglés
language eng
dc.relation.none.fl_str_mv Agencia Estatal de Investigación http://doi.org/10.13039/501100011033 Plan Estatal de Investigación Científica y Técnica y de Innovación 2021-2023 PID2021-126405OB-C31 DESARROLLO DE SENSORES MODULARES DE BAJO COSTE PARA SU USO EN IDENTIFICACION ESTRUCTURAL DE PUENTES SOMETIDOS A CARGAS QUASIESTATICAS
dc.rights.none.fl_str_mv open access
http://purl.org/coar/access_right/c_abf2
Attribution-NonCommercial-NoDerivatives 4.0 International
http://creativecommons.org/licenses/by-nc-nd/4.0/
dc.rights.openaire.fl_str_mv info:eu-repo/semantics/openAccess
rights_invalid_str_mv open access
http://purl.org/coar/access_right/c_abf2
Attribution-NonCommercial-NoDerivatives 4.0 International
http://creativecommons.org/licenses/by-nc-nd/4.0/
eu_rights_str_mv openAccess
dc.format.none.fl_str_mv text/html
application/pdf
dc.publisher.none.fl_str_mv Elsevier
publisher.none.fl_str_mv Elsevier
dc.source.none.fl_str_mv reponame:UPCommons. Portal del coneixement obert de la UPC
instname:Universitat Politècnica de Catalunya (UPC)
instname_str Universitat Politècnica de Catalunya (UPC)
reponame_str UPCommons. Portal del coneixement obert de la UPC
collection UPCommons. Portal del coneixement obert de la UPC
repository.name.fl_str_mv
repository.mail.fl_str_mv
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