Classification of power quality disturbances using wavelet and artificial neural network

Author

Rodríguez, A. ; Aguado, J. ; Martín, F. ; Muñoz, J. ; Medina, M. ; Ciumbulea, G.

Author_Institution

Dept. of Electr. Eng., Univ. of Malaga, Malaga, Spain

fYear

2010

Firstpage

1

Lastpage

7

Abstract

This paper presents a method of classification of power quality disturbances using Wavelet transforms combined with artificial neural network. Multi-resolution Wavelet analysis has been used as feature extractor, with different mothers Wavelet. Result comparison has been made in two levels: first, using different wavelet mothers, to determinate if the classification performance is better with a specific wavelet transform. The second level has been done using two differents Artificial Neural Network (ANN): backpropagation (BP) y Probabilistic Neural Network (PNN).

Keywords

backpropagation; feature extraction; neural nets; power supply quality; signal resolution; wavelet transforms; ANN; BP neural network; PNN; artificial neural network; backpropagation; feature extraction; multiresolution wavelet analysis; power quality disturbance classification; probabilistic neural network; wavelet transform; Hafnium; Artificial neural networks; Power Quality; Wavelet transform; disturbances classification;

fLanguage

English

Publisher

ieee

Conference_Titel

Power System Technology (POWERCON), 2010 International Conference on

Conference_Location

Hangzhou

Print_ISBN

978-1-4244-5938-4

Type

conf

DOI

10.1109/POWERCON.2010.5666537

Filename

5666537