Power Quality Disturbance Classification Using S-transform and Hidden Markov Model

Abstract

In this article, a combination method based on S-transform and the hidden Markov model is presented for power quality disturbance classification. S-transform is a new method that has been used in signal processing and power quality disturbance classification applications. S-transform not only has the advantages of both wavelet transform and fast Fourier transform but also characteristics superior than both mentioned transform methods. Besides, the hidden Markov model is a powerful and effective method on signal processing applications. This method computes the maximum likelihood probability between training and testing data signals for identification. The proposed method makes the classification more simple and accurate. The identification procedure has two major steps. First, features are extracted by S-transform, and in the second step, classification is done using a decision tree structure of hidden Markov models. Simulation results by simulated and experimental test signals reveal the robustness of proposed method and the possibility of using it for real applications.