DocumentCode
2996811
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
fYear
2000
fDate
2000
Firstpage
292
Lastpage
295
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;
fLanguage
English
Publisher
ieee
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
Type
conf
DOI
10.1109/APCCAS.2000.913491
Filename
913491
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