Generation of patterns of phenomena associated to power quality using the wavelet transform

This paper presents a model for the generation of patterns of phenomena associated to power quality in electric networks. This model is based on wavelet theory and on the use of wavelet tools available in MATLAB version 6.0. The method was developed by means of the DWT (discrete wavelet transform) analysis. The DWT decomposes the entry signal and any difference with the pure sine signal of 60 Hz with the corresponding amplitude is detected. Then the signal's power curve is analyzed and the deviation with the corresponding power curve of the fundamental signal is obtained. This deviation determines a pattern for each of the phenomena and it becomes easily recognizable and identifiable. Finally the foundation to train a neural network with these patterns is laid so the network can identify the phenomena, its risks and possible solutions.