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dc.contributor.authorAndrade Vieira, Rodrigo Josées-ES
dc.contributor.authorLietti, Matteoes-ES
dc.contributor.authorSanz Bobi, Miguel Ángeles-ES
dc.date.accessioned2016-01-15T11:26:27Z
dc.date.available2016-01-15T11:26:27Z
dc.date.issued2012-11-22es_ES
dc.identifier.urihttp://hdl.handle.net/11531/5512
dc.descriptionCapítulos en libroses_ES
dc.description.abstractes-ES
dc.description.abstractThis paper presents a new health threshold used in the MACOL model guided by a non-overpass of a stress limit for a component according to its health condition and technical and economical feasibility. This new health threshold will help to reschedule the programmed maintenance in a dynamical form according to the life evolution of the industrial component analyzed. The core of this study is the analysis of the degradation rate of each significant wind turbine failure mode in order to determine the health limit and the moment when the risk of failure is high. In the case that this health limit is close to being reached, maintenance actions are suggested to be executed by the maintenance model in order to keep the levels of stress at a desired point. Some real examples of application of these new concepts in failure modes of a wind turbine will be described.en-GB
dc.format.mimetypeapplication/pdfes_ES
dc.language.isoen-GBes_ES
dc.publisherUniversidad de Sevilla (Sevilla, España)es_ES
dc.rightses_ES
dc.rights.uries_ES
dc.sourceLibro: 2nd IFAC Workshop on Advanced Maintenance Engineering, Services and Technology - AMEST'2012, Página inicial: 187-192, Página final: 192es_ES
dc.subject.otherInstituto de Investigación Tecnológica (IIT)es_ES
dc.titleNew variable health threshold based on the life observed for improving the scheduled maintenance of a wind turbinees_ES
dc.typeinfo:eu-repo/semantics/bookPartes_ES
dc.description.versioninfo:eu-repo/semantics/publishedVersiones_ES
dc.rights.accessRightsinfo:eu-repo/semantics/restrictedAccesses_ES
dc.keywordses-ES
dc.keywordsComponent life monitoring, anomaly detection, maintenance, component stress, normal behaviour models, wind turbine diagnosis.en-GB


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