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Please use this identifier to cite or link to this item: http://acervodigital.unesp.br/handle/11449/73612
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dc.contributor.authorSouza, A. N.-
dc.contributor.authorRamos, C. C O-
dc.contributor.authorGastaldello, D. S.-
dc.contributor.authorNakamura, R. Y M-
dc.contributor.authorPapa, J. P.-
dc.date.accessioned2014-05-27T11:27:04Z-
dc.date.accessioned2016-10-25T18:38:42Z-
dc.date.available2014-05-27T11:27:04Z-
dc.date.available2016-10-25T18:38:42Z-
dc.date.issued2012-10-01-
dc.identifierhttp://dx.doi.org/10.1109/INES.2012.6249832-
dc.identifier.citationINES 2012 - IEEE 16th International Conference on Intelligent Engineering Systems, Proceedings, p. 209-212.-
dc.identifier.urihttp://hdl.handle.net/11449/73612-
dc.identifier.urihttp://acervodigital.unesp.br/handle/11449/73612-
dc.description.abstractIn 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.en
dc.format.extent209-212-
dc.language.isoeng-
dc.sourceScopus-
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 foresten
dc.typeoutro-
dc.contributor.institutionUniversidade Estadual Paulista (UNESP)-
dc.contributor.institutionUniversidade de São Paulo (USP)-
dc.description.affiliationDepartment of Electrical Engineering Universidade Estadual Paulista (UNESP), Bauru, São Paulo-
dc.description.affiliationDepartment of Electrical Engineering USP - University of São Paulo, Bauru, São Paulo-
dc.description.affiliationUnespDepartment of Electrical Engineering Universidade Estadual Paulista (UNESP), Bauru, São Paulo-
dc.identifier.doi10.1109/INES.2012.6249832-
dc.rights.accessRightsAcesso restrito-
dc.relation.ispartofINES 2012 - IEEE 16th International Conference on Intelligent Engineering Systems, Proceedings-
dc.identifier.scopus2-s2.0-84866646528-
Appears in Collections:Artigos, TCCs, Teses e Dissertações da Unesp

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