Study on the method of fault diagnosis in analog circuits based on new multi-class SVM

Abstract

Fault diagnosis in analog circuits is a comparatively front research topic. Firstly, the characteristics and the difficulties of fault diagnosis in analog circuits are introduced in this paper. Secondly, to overcome the defections of existing methods of SVM multiclass classification, a new method of SVM multiclass classification based on binary tree is presented. Aiming at the characteristics of fault diagnosis with finite samples and the difficulties of traditional mode identifying method based on gradual-close theory faces in fault pattern classifier, we used our new method of SVM multiclass classification to fault diagnosis of analog circuits. Finally, we also simulate on the fault diagnosis examples with the same training and test samples, and compare the results with that of neural networks method. The simulation results show the new method is efficient.