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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.date.accessioned2021-01-18T15:58:32Z
dc.date.available2021-01-18T15:58:32Z
dc.date.issued2021
dc.identifier.citationGarcía-Sánchez D. et al. (2021) Gradient-Boosting Applied for Proactive Maintenance System in a Railway Bridge. In: Rizzo P., Milazzo A. (eds) European Workshop on Structural Health Monitoring. EWSHM 2020. Lecture Notes in Civil Engineering, vol 127. Springer, Cham. https://doi.org/10.1007/978-3-030-64594-6_24en
dc.identifier.isbn978-3-030-64593-9en
dc.identifier.issn2366-2557en
dc.identifier.urihttp://hdl.handle.net/11556/1056
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.sponsorshipThe 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).en
dc.language.isoengen
dc.publisherSpringer, Chamen
dc.titleGradient-Boosting Applied for Proactive Maintenance System in a Railway Bridgeen
dc.typeconferenceObjecten
dc.identifier.doi10.1007/978-3-030-64594-6_24en
dc.relation.projectIDinfo:eu-repo/grantAgreement/EC/H2020/690660/EU/Risk based approaches for Asset inteGrity multimodal Transport Infrastructure ManagEment/RAGTIMEen
dc.relation.projectIDinfo:eu-repo/grantAgreement/EC/H2020/769373/EU/Future proofing strategies FOr RESilient transport networks against Extreme Events/FORESEEen
dc.rights.accessRightsembargoedAccessen
dc.subject.keywordsGradient-boostingen
dc.subject.keywordsCorrelationen
dc.subject.keywordsMulti-sensoren
dc.subject.keywordsBridgeen
dc.identifier.essn2366-2565en
dc.journal.titleLecture Notes in Civil Engineeringen
dc.page.final244en
dc.page.initial236en
dc.volume.number127en
dc.identifier.esbn978-3-030-64594-6en
dc.conference.titleEWSHM 2020: European Workshop on Structural Health Monitoringen


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