Classification of power quality disturbances using S-transform and Artificial Neural Networks

An automated classification based on S-transform as feature extraction tool and Artificial Neural Network as algorithm classifier is presented. The signals generated according to mathematical models have been used to obtain experimental results in two stages, first, with a data set with only simple disturbances and, later, including complex disturbances, more usual in real electrical systems. In both cases noise is added to the signals from 40dB to 20dB. At last, a data set with several disturbances, simple and complex, has been generated by simulation software based on electrical models, to test the implemented system. Evaluation results verifying the accuracy of the proposed method are presented.

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