Fast fault diagnosis in power transformers using optimum-path forest

dc.contributorUniversidade Estadual Paulista (UNESP)
dc.creatorSouza, A. N.
dc.creatorRamos, C. C O
dc.creatorGastaldello, D. S.
dc.creatorNakamura, R. Y M
dc.creatorPapa, J. P.
dc.date2014-05-27T11:27:04Z
dc.date2016-10-25T18:38:42Z
dc.date2014-05-27T11:27:04Z
dc.date2016-10-25T18:38:42Z
dc.date2012-10-01
dc.date.accessioned2017-04-06T02:01:47Z
dc.date.available2017-04-06T02:01:47Z
dc.identifierINES 2012 - IEEE 16th International Conference on Intelligent Engineering Systems, Proceedings, p. 209-212.
dc.identifierhttp://hdl.handle.net/11449/73612
dc.identifierhttp://acervodigital.unesp.br/handle/11449/73612
dc.identifier10.1109/INES.2012.6249832
dc.identifier2-s2.0-84866646528
dc.identifierhttp://dx.doi.org/10.1109/INES.2012.6249832
dc.identifier.urihttp://repositorioslatinoamericanos.uchile.cl/handle/2250/894410
dc.descriptionIn this paper we propose a fast and an accurate method for fault diagnosis in power transformers by means of Optimum-Path Forest (OPF) classifier. Since we applied Dissolved Gas Analysis (DGA), the samples have been labeled by IEEE/IEC standard, which was further analyzed by OPF and several other well known supervised pattern recognition techniques. The experiments have showed that OPF can achieve high recognition rates with low computational cost. © 2012 IEEE.
dc.languageeng
dc.relationINES 2012 - IEEE 16th International Conference on Intelligent Engineering Systems, Proceedings
dc.rightsinfo:eu-repo/semantics/closedAccess
dc.subjectComputational costs
dc.subjectDissolved gas analysis
dc.subjectOptimum-path forests
dc.subjectRecognition rates
dc.subjectSupervised pattern recognition
dc.subjectForestry
dc.subjectPattern recognition
dc.subjectPower transformers
dc.subjectExperimentation
dc.subjectPattern Recognition
dc.subjectPower Factor
dc.subjectTransformers
dc.titleFast fault diagnosis in power transformers using optimum-path forest
dc.typeOtro


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