Application of Wavelet Transform and Artificial Neural Network to Power Disturbance Identification

There are 3 procedures in power disturbance identification such as preprocessing,feature extraction and pattern identification.In this paper,the basic knowledge of wavelet transform and artificial neural network are introduced and the application of wavelet transform to feature extraction and the application of artificial neural network to pattern identification of power disturbance are studied.Then,simulations of power disturbance identification are carried on via the Matlab software.120 power disturbance samples are produced,feature extraction is carried on through wavelet transform,pattern identification is carried on through two kinds of neural network which are back propagation neural network(BPNN)and probabilistic Neural Network(PNN).When using the former neural network,the correct rate of identification is 87.5%,when using the later neural network,the correct rate of identification is 85%.The results of simulation manifest that the ability to identify power disturbance of the identification system is satisfactory,in which feature of the power disturbance is extracted through wavelet transform and pattern identification is carried on through back propagation neural network.