摘要
The theories of diagnosing nonlinear analog circuits by means of the transient response testing are studled. Wavelet analysis is made to extract the transient response signature of nonlinear circuits and compress the signature dada. The best wavelet function is selected based on the between-category total scatter of signature. The fault dictionary of nonlinear circuits is constructed based on improved back-propagation（BP） neural network. Experimental results demonstrate that the method proposed has high diagnostic sensitivity and fast fault identification and deducibility.
The theories of diagnosing nonlinear analog circuits by means of the transient response testing are studied. Wavelet analysis is made to extract the transient response signature of nonlinear circuits and compress the signature dada. The best wavelet function is selected based on the between-category total scatter of signature. The fault dictionary of nonlinear circuits is constructed based on improved back-propagation(BP) neural network. Experimental results demonstrate that the method proposed has high diagnostic sensitivity and fast fault identification and deducibility.
基金
This project was supported by the National Nature Science Foundation of China(60372001)
作者简介
Yin Shirong was born in 1974, Now she is a doctor candidate in University of Electronic Science and Technology of China. She majors in measuring and testing technology ＆ instruments. Her research interests include fault diagnosis of analog circuits and signal processing. E-mail：yinsr@126.com.Chen Guangju was born in 1940. Now he is a professor with University of Electronic Science and Technology of China. His research interests include diagnosis of integrated circuits and signal processing.Xie Yongle was born in 1969. Now he is an associate professor with University of Electronic Science and Technology of China. His research interest includes testing of integrated circuits.
