Analog circuit fault diagnosis based on particle swarm optimization SVM
基于粒子群算法优化支持向量机的模拟电路诊断

In order to improve the ccuracy of analog circuit fault diagnosis using support vectou machine SVMnetwork, this paper proposed the method based on particle swarm optimizationPSO and SVM. It preprocessed the response signals of the analog circuit using multiwavelet transform and obtained the optimal fault feature with better classification capacity using energy normalization. Then, after training the SVM by PSO, inputted the features into the ensemble SVM to identify different fault cases. Simulation results indicate that this method can effectively enhance the analog fault diagnostis accuracy.