Title :
Fault diagnosis of analog circuits with tolerances using artificial neural networks
Author :
Deng, Ying ; He, Yigang ; Sun, Yichuang
Author_Institution :
Coll. of Electr. & Inf. Eng., Hunan Univ., Changsha, China
Abstract :
This paper proposes a method for analog fault diagnosis using neural networks. The primary focus of the paper is to provide robust diagnosis using a mechanism to deal with the problem of component tolerances and reduce testing time. The proposed approach is based on the k-fault diagnosis method and artificial backward propagation neural network. Simulation results show that the method is robust and fast for fault diagnosis of analog circuits with tolerances
Keywords :
analogue circuits; circuit analysis computing; circuit testing; fault diagnosis; neural nets; ANN; analog circuits; analog fault diagnosis; artificial backward propagation neural network; component tolerances; k-fault diagnosis method; robust diagnosis; testing time reduction; Analog circuits; Artificial neural networks; Circuit faults; Circuit testing; Equations; Fault diagnosis; Helium; Neural networks; Robustness; Sun;
Conference_Titel :
Circuits and Systems, 2000. IEEE APCCAS 2000. The 2000 IEEE Asia-Pacific Conference on
Conference_Location :
Tianjin
Print_ISBN :
0-7803-6253-5
DOI :
10.1109/APCCAS.2000.913491
