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Fault detection and identification in a fuel cell system

dc.contributor.authorEscobet Canal, Antoni
dc.contributor.authorNebot Castells, M. Àngela
dc.contributor.otherUniversitat Politècnica de Catalunya. Departament d'Enginyeria Minera, Industrial i TIC
dc.contributor.otherUniversitat Politècnica de Catalunya. Departament de Ciències de la Computació
dc.date.accessioned2021-03-24T16:15:58Z
dc.date.issued2009
dc.identifier.citationEscobet, A.; Nebot, A. Fault detection and identification in a fuel cell system. A: International Conference of the Catalan Association for Artificial Intelligence. "Artificial intelligence research and development: proceedings of the 12th International Conference of the Catalan Association for Artificial Intelligence". IOS Press, 2009, p. 399-408. ISBN 978-1-60750-465-8. DOI 10.3233/978-1-60750-061-2-399.
dc.identifier.isbn978-1-60750-465-8
dc.identifier.urihttp://hdl.handle.net/2117/342400
dc.description.abstractIn this work a fault diagnosis system for non-linear plants based on fuzzy logic, called VisualBlock-FIR, is presented and applied to an energy generation system based on fuel cells. VisualBlock-FIR runs under the Simulink framework and enables early fault detection and identification. During fault detection, the fault diagnosis system should recognize that the system is not working properly. During fault identification, it should conclude which type of failure has occurred. The diagnosis results for some of the most frequent faults in fuel cell systems are presented.
dc.description.sponsorshipThis research was supported by the Consejo Interministerial de Ciencia y Tecnología under project TIN2006-08114.
dc.format.extent10 p.
dc.language.isoeng
dc.publisherIOS Press
dc.subjectÀrees temàtiques de la UPC::Informàtica::Automàtica i control
dc.subject.lcshFailure analysis (Engineering)
dc.subject.lcshFuel cells
dc.subject.lcshFuzzy logic
dc.subject.otherFault diagnosis system
dc.subject.otherFuel cell system
dc.subject.otherFuzzy logic
dc.subject.otherFuzzy inductive reasoning
dc.titleFault detection and identification in a fuel cell system
dc.typeConference report
dc.subject.lemacAnàlisi de fallades (Enginyeria)
dc.subject.lemacPiles de combustible
dc.subject.lemacLògica difusa
dc.contributor.groupUniversitat Politècnica de Catalunya. SIC - Sistemes Intel·ligents de Control
dc.contributor.groupUniversitat Politècnica de Catalunya. SOCO - Soft Computing
dc.identifier.doi10.3233/978-1-60750-061-2-399
dc.description.peerreviewedPeer Reviewed
dc.relation.publisherversionhttps://ebooks.iospress.nl/volumearticle/5460
dc.rights.accessRestricted access - publisher's policy
local.identifier.drac3343122
dc.description.versionPostprint (author's final draft)
dc.relation.projectidinfo:eu-repo/grantAgreement/MEC//TIN2006-08114/ES/DISEÑO DE UN SISTEMA DE APOYO A LA DECISION EN ONCOLOGIA CLINICA BASADO EN METODOS AVANZADOS DE SOFT COMPUTING Y VISUALIZACION/
dc.date.lift10000-01-01
local.citation.authorEscobet, A.; Nebot, A.
local.citation.contributorInternational Conference of the Catalan Association for Artificial Intelligence
local.citation.publicationNameArtificial intelligence research and development: proceedings of the 12th International Conference of the Catalan Association for Artificial Intelligence
local.citation.startingPage399
local.citation.endingPage408
dc.description.sdgObjectius de Desenvolupament Sostenible::7 - Energia Assequible i No Contaminant


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