PQ Event Classification Using Fuzzy Classifier

Abstract

The work presented here uses multiwavelet because of its inherent property to resolve the signal better than all single wavelets. Multiwavelets are based on more than one scaling function. The proposed methodology utilizes an enhanced resolving capability of multiwavelet to recognize power quality events. PQ events classification scheme is performed using multiwavelet transform for feature extraction and fuzzy classifier for classification. In proposed algorithm,statistical features (.i.e. mean, standard deviation, variation etc.) and energy of the signal at different decomposition levels have been considered as feature vectors. The performance of fuzzy classifier has been evaluated by using total 1000 PQ disturbance signals which are generated using the based model. The classification performance of different PQ events using proposed algorithm has been tested. The rate of average correct classification is about 99.95% for the different PQ disturbance signals and noisy disturbances.