CLASSIFICATION OF POWER QUALITY DISTURBANCES USING SVM

In this paper represented a new method for detection and classification of signal defects or disturbances. Before actual classification the database of signal is applied for wavelet transform. Two discrete wavelet transforms filters are used in the classification with feature extraction process. It improves the performance using pair of wavelet transform than single. For the classification of the signal disturbances Here used a support vector machine. For the computational purpose one can use binary decision tree is created and a support vector machine (SVM) classifier is trained for every node of the tree. It can be implemented using binary as ll as multiclass classification of SVM