Abstract:

In the process of the fault diagnosis of analog circuits,feature extraction and classifier design are two critical aspects.Most methods classified fault circuit via support vector machine(SVM) or neural network using extracted time signals and wavelet transforms.A new algorithm based on LMD and SVM is proposed to improve the diagnostic accuracy.The signal can be adaptively decomposed into a series of one-component AM-FM signal(PF) through using the LMD algorithm.The features of the normal or fault status of the circuit can be extracted.The features are classified using SVM to achieve the diagnostic accuracy.The result of simulation shows that the method is effective in the circuits fault diagnosis with an accuracy >98%.