Method for Analog Circuit Fault Diagnosis Based on GA Optimized SVM

A new method for analog circuit fault diagnosis is presented based on genetic algorithm optimized support vector machine multi-class decision tree (GADT-SVM). The design idea and algorithm principle of GADT-SVM is introduced firstly; then model of analog circuit is built by transfer function, and fault characteristic is picked-up by wavelet energy distribution of impulse response. Finally, fault samples are recognized by GADT-SVM. Experiment results show that our method can depress error accumulation phenomena of diagnosis and have stronger error control ability compared with the traditional DAG-SVM and DT-SVM.