EFFICIENT FAULT LOCATION IN UNDERGROUND DISTRIBUTION SYSTEMS THROUGH OPTIMUM-PATH FOREST

Autor(es)

Souza, Andre N. ^[1] ; da Costa, Jr., Pedro ^[1] ; da Silva, Paulo S. ^[1] ; Ramos, Caio C. O. ^[2] ; Papa, Joao P. ^[3]

Afiliação do(s) autor(es)

^[1] Sao Paulo State Univ, Dept Elect Engn, Bauru - Brazil

^[2] Univ Sao Paulo, Dept Elect Engn, Sao Paulo - Brazil

^[3] Sao Paulo State Univ, Dept Comp, Bauru - Brazil

• Tipo de documento: Artigo Científico
• Fonte: APPLIED ARTIFICIAL INTELLIGENCE; v. 26, n. 5, p. 503-515, 2012.
• Citações Web of Science: 0

Resumo

In this article we propose an efficient and 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 and a Bayesian classifier, but OPF was much more efficient than all classifiers for training, and the second fastest for classification. (AU)

• Processo FAPESP: 10/12398-0 - Desenvolvimento e avaliação de técnicas de localização de faltas em sistemas de distribuição subterrâneos
• Beneficiário: André Nunes de Souza
• Modalidade de apoio: Auxílio à Pesquisa - Regular