Planning low-error SHM strategy by constrained observability method

Structural identification using dynamical parameters (such as the natural vibration frequencies and mode shapes) is an important issue, especially in bridges or high-rise buildings. However, incorrect decisions could happen on the Structural Health Monitoring (SHM) strategy and the Structural System...

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Autores: Peng, Tian, Nogal, María, Casas Rius, Joan Ramon|||0000-0003-4473-4308, Turmo Coderque, José|||0000-0001-5001-2438
Tipo de recurso: artículo
Fecha de publicación:2021
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:2117/346480
Acceso en línea:https://hdl.handle.net/2117/346480
https://dx.doi.org/10.1016/j.autcon.2021.103707
Access Level:acceso abierto
Palabra clave:Structural health monitoring
Dynamic analysis
Observability method
Structural system identification
Decision tree
Monitorització de salut estructural
Àrees temàtiques de la UPC::Enginyeria civil::Materials i estructures
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dc.title.none.fl_str_mv Planning low-error SHM strategy by constrained observability method
title Planning low-error SHM strategy by constrained observability method
spellingShingle Planning low-error SHM strategy by constrained observability method
Peng, Tian
Structural health monitoring
Dynamic analysis
Observability method
Structural system identification
Structural health monitoring
Decision tree
Monitorització de salut estructural
Àrees temàtiques de la UPC::Enginyeria civil::Materials i estructures
title_short Planning low-error SHM strategy by constrained observability method
title_full Planning low-error SHM strategy by constrained observability method
title_fullStr Planning low-error SHM strategy by constrained observability method
title_full_unstemmed Planning low-error SHM strategy by constrained observability method
title_sort Planning low-error SHM strategy by constrained observability method
dc.creator.none.fl_str_mv Peng, Tian
Nogal, María
Casas Rius, Joan Ramon|||0000-0003-4473-4308
Turmo Coderque, José|||0000-0001-5001-2438
author Peng, Tian
author_facet Peng, Tian
Nogal, María
Casas Rius, Joan Ramon|||0000-0003-4473-4308
Turmo Coderque, José|||0000-0001-5001-2438
author_role author
author2 Nogal, María
Casas Rius, Joan Ramon|||0000-0003-4473-4308
Turmo Coderque, José|||0000-0001-5001-2438
author2_role author
author
author
dc.subject.none.fl_str_mv Structural health monitoring
Dynamic analysis
Observability method
Structural system identification
Structural health monitoring
Decision tree
Monitorització de salut estructural
Àrees temàtiques de la UPC::Enginyeria civil::Materials i estructures
topic Structural health monitoring
Dynamic analysis
Observability method
Structural system identification
Structural health monitoring
Decision tree
Monitorització de salut estructural
Àrees temàtiques de la UPC::Enginyeria civil::Materials i estructures
description Structural identification using dynamical parameters (such as the natural vibration frequencies and mode shapes) is an important issue, especially in bridges or high-rise buildings. However, incorrect decisions could happen on the Structural Health Monitoring (SHM) strategy and the Structural System Identification (SSI) analysis that makes the sometimes expensive and time-consuming process useless due to the large uncertainty of the resulting estimations. This paper discusses the role of the SHM strategy and the SSI analysis based on the constrained observability method (COM) and decision trees (DT) in reducing the estimation error. Here, the COM uses subsets of natural frequencies and/or modal-shapes to deal with the nonlinearity of the SSI derived from the operational aspects of the methods, and combines the unknown items including frequencies and mode shapes into an optimization process. Next, a decision-support tool based on decision trees is applied to help engineers to establish the best SHM + SSI strategy yielding the most accurate estimations. The principle and steps of this new method, the combination of constrained observability m,ethod and decision trees, are presented for the first time. After that, a numerical model of a bridge case is used to show how to choose the optimal strategy, when factors such as the structure layout, span length, measurement set, and parameters of the COM are included as decision variables. The importance ranking of these four factors is the layout, measurement set, parameters of the COM, and length through the sensitivity analysis of the COM estimated. Last, a real bridge is used to validate this methodology under the undamaged and damaged scenarios by comparing an Error Index, which shows the optimal SHM + SSI strategy works well no matter the bridge is damaged or not. The presented analysis leads to significant insights that can help the decision-making of the optimal SHM + SSI strategy, avoiding erroneous decisions if this tool is not used beforehand.
publishDate 2021
dc.date.none.fl_str_mv 2021
2021-07-01
2021
2021-06-01
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/2117/346480
https://dx.doi.org/10.1016/j.autcon.2021.103707
url https://hdl.handle.net/2117/346480
https://dx.doi.org/10.1016/j.autcon.2021.103707
dc.language.none.fl_str_mv Inglés
eng
language_invalid_str_mv Inglés
language eng
dc.relation.none.fl_str_mv Ministerio de Economía y Competitividad http://doi.org/10.13039/501100003329 BIA2013-47290-R SISTEMA DE APOYO A LA TOMA DE DECISIONES DURANTE EL CICLO DE VIDA DE LAS INFRAESTRUCTURAS: SMART-INFRASTRUCTURES
Agencia Estatal de Investigación http://doi.org/10.13039/501100011033 Plan Estatal de Investigación Científica y Técnica y de Innovación 2013-2016 BIA2017-86811-C2-1-R MODELOS ESTRUCTURALES PARA LA GESTION EFICIENTE DE INFRAESTRUCTURAS: SMART BIM MODELS
dc.rights.none.fl_str_mv open access
http://purl.org/coar/access_right/c_abf2
Attribution-NonCommercial-NoDerivatives 4.0 International
https://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
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Attribution-NonCommercial-NoDerivatives 4.0 International
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eu_rights_str_mv openAccess
dc.format.none.fl_str_mv application/pdf
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)
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spelling Planning low-error SHM strategy by constrained observability methodPeng, TianNogal, MaríaCasas Rius, Joan Ramon|||0000-0003-4473-4308Turmo Coderque, José|||0000-0001-5001-2438Structural health monitoringDynamic analysisObservability methodStructural system identificationStructural health monitoringDecision treeMonitorització de salut estructuralÀrees temàtiques de la UPC::Enginyeria civil::Materials i estructuresStructural identification using dynamical parameters (such as the natural vibration frequencies and mode shapes) is an important issue, especially in bridges or high-rise buildings. However, incorrect decisions could happen on the Structural Health Monitoring (SHM) strategy and the Structural System Identification (SSI) analysis that makes the sometimes expensive and time-consuming process useless due to the large uncertainty of the resulting estimations. This paper discusses the role of the SHM strategy and the SSI analysis based on the constrained observability method (COM) and decision trees (DT) in reducing the estimation error. Here, the COM uses subsets of natural frequencies and/or modal-shapes to deal with the nonlinearity of the SSI derived from the operational aspects of the methods, and combines the unknown items including frequencies and mode shapes into an optimization process. Next, a decision-support tool based on decision trees is applied to help engineers to establish the best SHM + SSI strategy yielding the most accurate estimations. The principle and steps of this new method, the combination of constrained observability m,ethod and decision trees, are presented for the first time. After that, a numerical model of a bridge case is used to show how to choose the optimal strategy, when factors such as the structure layout, span length, measurement set, and parameters of the COM are included as decision variables. The importance ranking of these four factors is the layout, measurement set, parameters of the COM, and length through the sensitivity analysis of the COM estimated. Last, a real bridge is used to validate this methodology under the undamaged and damaged scenarios by comparing an Error Index, which shows the optimal SHM + SSI strategy works well no matter the bridge is damaged or not. The presented analysis leads to significant insights that can help the decision-making of the optimal SHM + SSI strategy, avoiding erroneous decisions if this tool is not used beforehand.This work was mainly funded by the Chinese Scholarship Council through its program (No. 201808390083), which has been provided to Mrs. Peng. It is also to be noted that this work was partially funded by the Spanish Ministry of Economy and Competitiveness for the funding provided through the research projects BIA2013-47290-R and BIA2017-86811-C2-1-R founded with FEDER funds and directed by Professor José Turmo. Authors are also indebted to the Secretaria d’ Universitats i Recerca de la Generalitat de Catalunya for the funding provided through Agaur (2017 SGR 1481).Peer Reviewed20212021-07-0120212021-06-01journal articlehttp://purl.org/coar/resource_type/c_6501VoRhttp://purl.org/coar/version/c_970fb48d4fbd8a85info:eu-repo/semantics/articleapplication/pdfhttps://hdl.handle.net/2117/346480https://dx.doi.org/10.1016/j.autcon.2021.103707reponame:UPCommons. Portal del coneixement obert de la UPCinstname:Universitat Politècnica de Catalunya (UPC)InglésengMinisterio de Economía y Competitividad http://doi.org/10.13039/501100003329 BIA2013-47290-R SISTEMA DE APOYO A LA TOMA DE DECISIONES DURANTE EL CICLO DE VIDA DE LAS INFRAESTRUCTURAS: SMART-INFRASTRUCTURESAgencia Estatal de Investigación http://doi.org/10.13039/501100011033 Plan Estatal de Investigación Científica y Técnica y de Innovación 2013-2016 BIA2017-86811-C2-1-R MODELOS ESTRUCTURALES PARA LA GESTION EFICIENTE DE INFRAESTRUCTURAS: SMART BIM MODELSopen accesshttp://purl.org/coar/access_right/c_abf2Attribution-NonCommercial-NoDerivatives 4.0 Internationalhttps://creativecommons.org/licenses/by-nc-nd/4.0/info:eu-repo/semantics/openAccessoai:upcommons.upc.edu:2117/3464802026-05-27T15:37:01Z
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