Application of wavelet theory to power distribution systems for fault detection

摘要

In this paper an investigation of the wavelet transform as a means of creating a feature extractor for Artificial Neural Network (ANN) training is presented. The study includes a teresstrial-based 3 phase delta power distribution system. Faults were injected into the system and data was obtained from experimentation. Graphical representations of the feature extractors obtained in the time domain, the frequency domain and the wavelet domain are presented to ascertain the superiority of the wavelet ''reform feature extractor.