A kind integrated adaptive fuzzy neural network tolerance analog circuit fault diagnosis method

Abstract

Combining fuzzy theory and neural network is an effective way to be applied in fault diagnosis of analog circuit. For tolerance analog circuit fault, this paper proposed a kind new based on integrated adaptive fuzzy neural network the diagnosis method. The method first uses wavelet transform to extract the signal from the output sample, and characteristics of fault feature vectors are normalized. Then it uses the principal element analysis to reduce the fault sample dimension, the network architecture can be simplified, the computation complexity can be reduced. Afterward training and testing integrated adaptive fuzzy neural network with the preprocessed fault characteristic data. Experimentation indicates that the method has higher diagnosis nicety rate and effectively solves fault tolerance of ambiguity and problems.