Educational Software for Power Quality Analysis

This paper presents educational software that allows users to generate, detect and classify electrical power disturbance signals using a Wavelet Transform and Neural Networks based algorithm. This software includes four main modules: a) Signal Acquisition Module that allows the incorporation of waveforms stored in a data base; b) Generation Module which permits the generation of diverse disturbed waveforms; c) Detections Module provides tools to analyze different disturbance detection algorithms and d) Classification Module that determines the disturbance type using different pattern classification methods.