Classification of events in distribution networks using autonomous neural models
This paper presents a method for automatic classification of faults and events related to quality of service in electricity distribution networks. The method consists in preprocessing event oscillographies using the wavelet transform and then classifying them using autonomous neural models. In the p...
| Principais autores: | Lazzaretti, Andre Eugênio, Ferreira, Vitor Hugo, Vieira Neto, Hugo, Riella, Rodrigo Jardim, Omori, Julio Shigeaki |
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| Formato: | Trabalho Apresentado em Evento |
| Idioma: | Inglês |
| Publicado em: |
Curitiba
2013
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| Assuntos: | |
| Acesso em linha: |
http://repositorio.utfpr.edu.br/jspui/handle/1/658 http://dx.doi.org/10.1109/ISAP.2009.5352812 |
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| Resumo: |
This paper presents a method for automatic classification of faults and events related to quality of service in electricity distribution networks. The method consists in preprocessing event oscillographies using the wavelet transform and then classifying them using autonomous neural models. In the preprocessing stage, the energy present in each sub-band of the wavelet domain is computed in order to compose input feature vectors for the classification stage. The classifiers investigated are based in Multi-Layer Perceptron (MLP) feed-forward artificial neural networks and Support Vector Machines (SVM), which automatically promote input selection and structure complexity control simultaneously. Experiments using simulated data show promising results for the proposed application. |
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