Faults Diagnosis Approach for Analog Circuit Based on Complex Cross-Wavelet Transform

A new method for fault feature extraction problem in analog circuit diagnosis is presented using collaborative analysis of relative amplitude and phase based on complex cross-wavelet transform, and the sensitive information extraction algorithm is built according to the characteristics of the wavelet transform. Using complex cross-wavelet transform, fault signature can be effectively extracted at different frequency and time scales. The relative amplitude and the relative phase are used to characterize analog circuit faults in signal energy and signal delay, respectively. Due to the influence of component tolerance, Monte-Carlo simulation is used to analyze the normal circuit. The result of simulation shows that the catastrophic and parametric fault diagnosis problem can be effectively solved through the proposed method.