conferenceObject
Classification of events in distribution networks using autonomous neural models
Fecha
2009-11Registro en:
978-1-4244-5097-8
Autor
Lazzaretti, Andre Eugênio
Ferreira, Vitor Hugo
Vieira Neto, Hugo
Riella, Rodrigo Jardim
Omori, Julio Shigeaki
Resumen
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.