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dc.contributor.authorMartínez Reyes, Jimmy Arturo
dc.contributor.authorGómez-Pau, Álvaro
dc.contributor.authorRiba Ruiz, Jordi-Roger
dc.contributor.authorMoreno Eguilaz, Juan Manuel
dc.contributor.otherUniversitat Politècnica de Catalunya. Doctorat en Enginyeria Elèctrica
dc.contributor.otherUniversitat Politècnica de Catalunya. Departament d'Enginyeria Elèctrica
dc.contributor.otherUniversitat Politècnica de Catalunya. Departament d'Enginyeria Electrònica
dc.date.accessioned2020-12-22T13:49:22Z
dc.date.available2022-12-16T01:29:24Z
dc.date.issued2020-12-16
dc.identifier.citationMartinez, J. [et al.]. On-line health condition monitoring of power connectors focused on predictive maintenance. "IEEE transactions on power delivery", 16 Desembre 2020, p. 1-8.
dc.identifier.issn0885-8977
dc.identifier.urihttp://hdl.handle.net/2117/334802
dc.description.abstractElectrical power connectors are critical points of electrical networks. Failure in high-voltage connectors may result in major power outages, safety risks and important economic consequences. Therefore, there is an imperious need to tackle such issue by developing suitable on-line condition monitoring strategies to minimize the aforementioned problems and to ease the application of predictive maintenance tasks. This work develops an on-line condition monitoring method to predict early failures in power connectors from data acquired on-line (electric current and voltage drop across the connector, and temperature) to determine the instantaneous value of the connector resistance, since it is used as a signature or indicator of its health condition. The proposed approach combines a parametric degradation model of the resistance of the connector, whose parameters are identified by means of the Markov chain Monte Carlo stochastic method, which also provides the confidence intervals of the electrical resistance. This fast approach allows an on-line diagnosis of the health condition of the connector, anticipating its failure and thus, easing the application of predictive maintenance plans. Laboratory results emulating the ageing conditions of the connectors prove the suitability and feasibility of the proposed approach, which could be applied to other power products and apparatus.
dc.format.extent8 p.
dc.language.isoeng
dc.publisherInstitute of Electrical and Electronics Engineers (IEEE)
dc.rightsAttribution-NonCommercial-NoDerivs 3.0 Spain
dc.rights.urihttp://creativecommons.org/licenses/by-nc-nd/3.0/es/
dc.subjectÀrees temàtiques de la UPC::Enginyeria elèctrica
dc.subject.lcshElectric networks
dc.subject.otherPower connectors
dc.subject.otherParameter identification
dc.subject.otherOnline monitoring
dc.subject.otherContact resistance
dc.subject.otherCondition monitoring
dc.subject.otherFault diagnosis
dc.subject.otherPredictive maintenance
dc.titleOn-line health condition monitoring of power connectors focused on predictive maintenance
dc.typeArticle
dc.subject.lemacXarxes elèctriques
dc.contributor.groupUniversitat Politècnica de Catalunya. MCIA - Motion Control and Industrial Applications Research Group
dc.identifier.doi10.1109/TPWRD.2020.3045289
dc.relation.publisherversionhttps://ieeexplore.ieee.org/document/9296389
dc.rights.accessOpen Access
local.identifier.drac30025960
dc.description.versionPostprint (author's final draft)
local.citation.authorMartinez, J.; Gómez-Pau, Á.; Riba, J.; Moreno-Eguilaz, J.M.
local.citation.publicationNameIEEE transactions on power delivery
local.citation.startingPage1
local.citation.endingPage8


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