An Effective S-transform Feature Extraction Method for Classification of Power Quality Disturbance Signals

This paper presents a S-transform effective feature extraction method for power quality (PQ) disturbance classification problem. Firstly, S-transform technique is used to extract the significant features of distorted signal. Then, an optimum combination of the most useful features is identified for increasing the accuracy of classification. Features extracted by using the S-transform are applied as input to support vector machines (SVM) for automatic classification of the power quality (PQ) disturbances that solves a relatively complex problem. Seven single disturbances and six complex disturbances selected as reference are considered for the classification. Sensitivity of proposed classifier under different noise conditions is investigated. The analysis and results show that the classifier can effectively classify different PQ disturbances.