一种模拟电路的支持向量机故障诊断方法

系统地提出了模拟电路的最小二乘小波支持向量机故障诊断方法。从测试点得到各种故障状态下的输出电压信号，对输出电压信号进行小波去噪，对信号进行小波分解获取多尺度的低频系数和高频系数，并对小波系数进行处理从而提取出故障特征量，以此作为学习样本来训练最小二乘小波支持向量机，确定其模拟电路故障诊断的模型。雷达系统电路仿真结果表明了模拟电路的小波变换和最小二乘小波支持向量机故障诊断方法取得了较好的效果。

A Fault Diagnosis Approach for Analog Circuits with Support Vector Machines

Based on least squares wavelet support vector machines, a systematic approach for fault diagnosis of analog circuits is presented. Firstly, output voltage signals under faulty conditions are obtained from analog circuit test points and noise is removed from signals with wavelet transformation. Then wavelet coefficients of output voltage signals are gained by wavelet decomposition, and faulty feature vectors are extracted from the coefficients. After training the least squares wavelet support vector machines by faulty feature vectors, the least squares wavelet support vector machines model of the analog circuit fault diagnosis system is built. The simulation result shows the fault diagnosis method of the analog circuits with wavelet transformation and least squares wavelet support vector machines is effective.