基于复互小波分析的模拟电路故障诊断方法

摘要

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.%针对模拟电路故障诊断研究中故障特征提取的难题,提出基于复互小波变换的相对幅度-相对相位协同分析的新方法,并根据复互小波变换的特点构建了故障敏感信息提取算法,使用复互小波变换能同时提取模拟电路在不同频率和时间尺度上的故障特征,并且相对幅度和相对相位信息分别从信号“能量”和“时间延迟”两个不同角度表征模拟电路的故障信息.该方法同时使用了蒙特卡洛方法构建正常电路元器件的容差范围,仿真实验结果表明该方法可以有效地解决模拟电路中灾难型和参教型故障诊断问题.