Analog Circuit Soft Fault Diagnosis Based on Wavelet Analysis and Fuzzy Clustering

A method of analog circuit fault diagnosis based on extracting fault features by using wavelet decomposition and fuzzy clustering is presented in this paper.This approach performs wavelet decomposition on the acquired output signals of the test circuit and takes the reconstructing wavelet coefficients as the fault feature values,then using the method of fuzzy clustering based on markov distance to division the test matrix to reduce the dimensions of the test matrix,finally the obtained test matrix are inputted into the neural network for fault diagnosis.The simulation result show是that the proposed method can effectively extract the fault feature and obtain well accuracy of analog circuit fault diagnosis.