DETECTION AND CLASSIFICATION OF POWER QUALITY DISTURBANCES USING WAVELET TRANSFORMS AND PROBABLISTIC NEURAL NETWORKS

摘要: The use of sensitive electronic equipments is on the rise lately and power quality studies have progressed a lot. Detection classification signals greater importance both in case Power denoising. This paper proposes detection technique for several disturbances, by introspecting energy distorted at different resolutions using Multiresolution Analysis (MRA) Discrete wavelet transform (DWT) .i.e. Energy Difference MRA (EDMRA) used .This employed to extract distribution features levels resolution. Db4 mother decompose signal. disturbances are identified based difference disturbance signal with pure sinusoidal 50Hz each decomposition level. forms feature vector that fed input nodes probabilistic neural network which classifies disturbances. To validate efficiency preciseness proposed method simulation results analyzed. Keywords— Quality, Wavelet Energy, Probabilistic Neural Network (PNN), (MRA), Multi resolution (EDMRA).