Fault location in underground systems through optimum-path forest

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dc.contributor.authorSouza, André N. [UNESP]
dc.contributor.authorDa Costa Jr., Pedro [UNESP]
dc.contributor.authorDa Silva, Paulo S. [UNESP]
dc.contributor.authorRamos, Caio C. O.
dc.contributor.authorPapa, João Paulo [UNESP]
dc.contributor.institutionUniversidade Estadual Paulista (Unesp)
dc.contributor.institutionUniversidade de São Paulo (USP)
dc.date.accessioned2014-05-27T11:26:20Z
dc.date.available2014-05-27T11:26:20Z
dc.date.issued2011-12-21
dc.description.abstractIn this paper we propose an accurate method for fault location in underground distribution systems by means of an Optimum-Path Forest (OPF) classifier. We applied the Time Domains Reflectometry method for signal acquisition, which was further analyzed by OPF and several other well known pattern recognition techniques. The results indicated that OPF and Support Vector Machines outperformed Artificial Neural Networks classifier. However, OPF has been much more efficient than all classifiers for training, and the second one faster for classification. © 2011 IEEE.en
dc.description.affiliationDepartment of Electrical Engineering UNESP - Univ. Estadual Paulista, São Paulo, São Paulo
dc.description.affiliationDepartment of Electrical Engineering USP - University of São Paulo, São Paulo, São Paulo
dc.description.affiliationDepartment of Computing UNESP - Univ. Estadual Paulista, Bauru, São Paulo
dc.description.affiliationUnespDepartment of Electrical Engineering UNESP - Univ. Estadual Paulista, São Paulo, São Paulo
dc.description.affiliationUnespDepartment of Computing UNESP - Univ. Estadual Paulista, Bauru, São Paulo
dc.identifierhttp://dx.doi.org/10.1109/ISAP.2011.6082204
dc.identifier.citation2011 16th International Conference on Intelligent System Applications to Power Systems, ISAP 2011.
dc.identifier.doi10.1109/ISAP.2011.6082204
dc.identifier.lattes9039182932747194
dc.identifier.scopus2-s2.0-83655197667
dc.identifier.urihttp://hdl.handle.net/11449/73076
dc.language.isoeng
dc.relation.ispartof2011 16th International Conference on Intelligent System Applications to Power Systems, ISAP 2011
dc.rights.accessRightsAcesso aberto
dc.sourceScopus
dc.subjectFault Location
dc.subjectOptimum-Path Forest
dc.subjectPattern Recognition
dc.subjectUnderground Systems
dc.subjectArtificial Neural Network
dc.subjectPattern recognition techniques
dc.subjectReflectometry
dc.subjectSignal acquisitions
dc.subjectTime domain
dc.subjectUnderground distribution system
dc.subjectUnderground systems
dc.subjectElectric fault location
dc.subjectForestry
dc.subjectIntelligent systems
dc.subjectNeural networks
dc.subjectPattern recognition
dc.subjectPower transmission
dc.subjectSignal processing
dc.subjectTime domain analysis
dc.subjectAlgorithms
dc.subjectClassification
dc.subjectDefects
dc.subjectElectric Power Distribution
dc.subjectForests
dc.subjectNeural Networks
dc.titleFault location in underground systems through optimum-path foresten
dc.typeTrabalho apresentado em evento
dcterms.licensehttp://www.ieee.org/publications_standards/publications/rights/rights_policies.html
unesp.author.lattes9039182932747194
unesp.author.lattes8212775960494686[1]
unesp.author.orcid0000-0002-8617-5404[1]
unesp.campusUniversidade Estadual Paulista (Unesp), Faculdade de Ciências, Baurupt
unesp.departmentComputação - FCpt

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