Fault Classification in Power Distribution Systems Using Multiresolution Analysis and a Fuzzy-ARTMAP Neural NetworkAnalysis and a Fuzzy-ARTMAP Neural Network

Autor: Haislan Bernardes, Carlos R. Minussi, Mauro S. Tonelli-Neto
Přispěvatelé: Ciencia e Tecnologia de Sao Paulo, Universidade Estadual Paulista (UNESP)
Rok vydání: 2021
Předmět:
Zdroj: Scopus
Repositório Institucional da UNESP
Universidade Estadual Paulista (UNESP)
instacron:UNESP
ISSN: 1548-0992
DOI: 10.1109/tla.2021.9475615
Popis: Made available in DSpace on 2022-05-01T08:15:10Z (GMT). No. of bitstreams: 0 Previous issue date: 2021-11-01 This paper presents a tool for the detection and classification of short-circuits in electric power distribution systems, which is based on the combined use of multi-resolution analysis and Fuzzy-ARTMAP neural network. The multiresolution analysis allows the identification of singularities in the waveforms and the ART family network guarantees to the classifier the ability to continuously learn without losing the previously acquired knowledge. The entire diagnosis procedure is performed in a single step, reducing the computational effort. The efficiency of the system is verified by a direct accuracy analysis, and by a comparison between the Fuzzy-ARTMAP and the EuclideanARTMAP. Results show that the system is efficient and robust, being able to detect and classify 100% of the electrical faults considering the test that were performed. Instituto Federal de Educacao Ciencia e Tecnologia de Sao Paulo, Sao Paulo Universidade Estadual Paulista, Sao Paulo Universidade Estadual Paulista, Sao Paulo
Databáze: OpenAIRE