Power Quality Disturbance Classification Based on S Transform and Fourier Transform

TLDR: In this article, a new detection and classification method of power quality disturbances based on S transform, interpolating windowed fast Fourier transform (FFT) and probabilistic neural network(PNN) was proposed.

Abstract: A new detection and classification method of power quality disturbances based on S transform,interpolating windowed fast Fourier transform(FFT) and probabilistic neural network(PNN) was proposed.S transform and interpolating windowed FFT was first applied to perform time-frequency analysis on power quality disturbance samples,and the features can then be extracted from the results.These features are then used to train a PNN for disturbance classification.Results of applying the trained PNN on a test set with common power quality disturbances show that the method has relatively high classification accuracy.In the presence of smaller training set,higher noise level,and multiple types of disturbances,the proposed method can still achieve good classification.