基于小波神经网络局部放电模式识别方法的实验研究

An Experiment Study of Partial Discharge Pattern Recognition Method Based on Wavelet Neural Networks

针对局部放电信号频率的特点,在小波神经网络基础上,构造一个改进型小波神经网 络,并把信号在小波基的否同尺度和位移上展开,得到信号在不同尺度下的小波细节系数,将其输 入到该小波网络进行局部放电模式识别．实验仿真得出,识别的相对误差范围为0．1％-3．9％．

Considering the frequency characteristic of the partial discharge signal, on the basis ot the wavelet neural network, an improved wavelet neural network is constructed. Signals are transformed by wavelet basis on different scales and displacements, and the wavelet detail coefficients are obtained under the different scales, finally sending them to the wavelet neural network to complete pattern recognition. Experiment simulations obtain the recognition relative errors range between 0. 1% and 3.9%.