Gradient-Boosting Applied for Proactive Maintenance System in a Railway Bridge

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dc.contributor.authorGarcía-Sánchez, David
dc.contributor.authorIglesias, Francisco
dc.contributor.authorDiez, Jesus
dc.contributor.authorPiñero, Iñaki
dc.contributor.authorFernández-Navamuel, Ana
dc.contributor.authorSánchez, Diego Zamora
dc.contributor.authorJiménez-Fernandez, José Carlos
dc.contributor.editorRizzo, Piervincenzo
dc.contributor.editorMilazzo, Alberto
dc.contributor.institutionTecnalia Research & Innovation
dc.contributor.institutionE&I SEGURAS Y RESILIENTES
dc.date.issued2021
dc.descriptionPublisher Copyright: © 2021, Springer Nature Switzerland AG.
dc.description.abstractThis article contributes in the research direction of the application of Machine Learning techniques in bridge safety assessment and it lays basis to further improve the accuracy of safety assessment including analysis of real data. The communication puts forward the process and model of scale measured points correlation of bridge monitoring system on the frequency domain as a tactic to control the influence of a railway device (crossing) located on the top deck of a railway bridge. The process and model are put forward mainly for the characteristics of the damage detection for long-term assessment, going from an intensive multi-sensor monitoring system to a softer one. Finally, a Gradient-Boosting multi-regressor method has been developed to be easily implemented in a warning system that provides predictive skills to the current preventive maintenance strategy. The method is validated by simulating the undamaged and abnormal scenarios with Monte Carlo method.en
dc.description.statusPeer reviewed
dc.format.extent9
dc.format.extent1820552
dc.identifier.citationGarcía-Sánchez , D , Iglesias , F , Diez , J , Piñero , I , Fernández-Navamuel , A , Sánchez , D Z & Jiménez-Fernandez , J C 2021 , Gradient-Boosting Applied for Proactive Maintenance System in a Railway Bridge . in P Rizzo & A Milazzo (eds) , unknown . vol. 127 , 2366-2557 , Springer, Cham , pp. 236-244 , European Workshop on Structural Health Monitoring, EWSHM 2020 , 6/07/20 . https://doi.org/10.1007/978-3-030-64594-6_24
dc.identifier.citationconference
dc.identifier.doi10.1007/978-3-030-64594-6_24
dc.identifier.isbn978-3-030-64593-9
dc.identifier.isbn9783030645939
dc.identifier.isbn978-3-030-64594-6
dc.identifier.otherresearchoutputwizard: 11556/1056
dc.identifier.urlhttp://www.scopus.com/inward/record.url?scp=85101194790&partnerID=8YFLogxK
dc.language.isoeng
dc.publisherSpringer, Cham
dc.relation.ispartofunknown
dc.relation.ispartofseries2366-2557
dc.rightsinfo:eu-repo/semantics/restrictedAccess
dc.subject.keywordsGradient-boosting
dc.subject.keywordsCorrelation
dc.subject.keywordsMulti-sensor
dc.subject.keywordsBridge
dc.subject.keywordsGradient-boosting
dc.subject.keywordsCorrelation
dc.subject.keywordsMulti-sensor
dc.subject.keywordsBridge
dc.subject.keywordsCivil and Structural Engineering
dc.subject.keywordsProject ID
dc.subject.keywordsinfo:eu-repo/grantAgreement/EC/H2020/690660/EU/Risk based approaches for Asset inteGrity multimodal Transport Infrastructure ManagEment/RAGTIME
dc.subject.keywordsinfo:eu-repo/grantAgreement/EC/H2020/769373/EU/Future proofing strategies FOr RESilient transport networks against Extreme Events/FORESEE
dc.subject.keywordsinfo:eu-repo/grantAgreement/EC/H2020/690660/EU/Risk based approaches for Asset inteGrity multimodal Transport Infrastructure ManagEment/RAGTIME
dc.subject.keywordsinfo:eu-repo/grantAgreement/EC/H2020/769373/EU/Future proofing strategies FOr RESilient transport networks against Extreme Events/FORESEE
dc.subject.keywordsFunding Info
dc.subject.keywordsThe work presented here has received funding from Horizon 2020, the EU’s Framework Programme for Research and Innovation, under grant agreement number 690660 (Project: RAGTIME), and also under grant agreement number 769373 (Project: FORESEE).
dc.subject.keywordsThe work presented here has received funding from Horizon 2020, the EU’s Framework Programme for Research and Innovation, under grant agreement number 690660 (Project: RAGTIME), and also under grant agreement number 769373 (Project: FORESEE).
dc.titleGradient-Boosting Applied for Proactive Maintenance System in a Railway Bridgeen
dc.typeconference output
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