Combined VMD-SVM based feature selection method for classification of power quality events
Different types of power quality disturbances are discriminated from each other. VMD and ST are used for extraction of dominant features. SVM with simple structure and few adjustable parameters is used as the classifier core. The generalization capability and detection accuracy of the proposed method are increased by elimination of redundant features by using different feature selection methods. The start and end points of PQ events can be detected accurately.
feature selection pattern recognition support vector machines signal analysis s-transform variational mode decomposition