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dc.contributor.authorAndrade Vieira, Rodrigo Josées-ES
dc.contributor.authorSanz Bobi, Miguel Ángeles-ES
dc.date.accessioned2016-01-15T11:16:37Z
dc.date.available2016-01-15T11:16:37Z
dc.date.issued2013-01-01es_ES
dc.identifier.issn0003-2506es_ES
dc.identifier.urihttp://hdl.handle.net/11531/5003
dc.descriptionArtículos en revistases_ES
dc.description.abstractThe use of renewable energy is essential for global development and wind power is one of the most attractive among them. Wind turbines occupy a central role in this context and they have had a significant technological development in the last years. Usually the maintenance applied to them is based on preventive models. In the case of critical components is desirable to have a more accurately and frequently enough health forecasting to determine its condition and make decisions instantly before the fault develops. This paper describes a method for estimating health condition indicators based on the evolution of the system life (normal and overload behavior). The idea is that the modeling of these indicators associated with the wind turbine components failure modes help to reschedule dynamically the maintenance plan according to its reallife developments.es-ES
dc.description.abstracten-GB
dc.format.mimetypeapplication/pdfes_ES
dc.language.isoes-ESes_ES
dc.sourceRevista: Anales de Mecánica y Electricidad, Periodo: 1, Volumen: online, Número: I, Página inicial: 17, Página final: 26es_ES
dc.subject.otherInstituto de Investigación Tecnológica (IIT)es_ES
dc.titleEvaluación de indicadores de la condición de aerogeneradoreses_ES
dc.typeinfo:eu-repo/semantics/articlees_ES
dc.description.versioninfo:eu-repo/semantics/publishedVersiones_ES
dc.rights.holderes_ES
dc.rights.accessRightsinfo:eu-repo/semantics/openAccesses_ES
dc.keywordsWind turbines, normal behavior models, anomaly detection, failure mode risk indicator, maintenance.es-ES
dc.keywordsen-GB


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