Title :
On the application of artificial neural networks to fault diagnosis in analog circuits with tolerances
Author :
Ying, Deng ; Yigang, He
Author_Institution :
Coll. of Electr. & Inf. Eng., Hunan Univ., Changsha, China
Abstract :
This paper proposes a method for analog fault diagnosis by adopting 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 to reduce the testing time. The proposed approach is based on the k-fault diagnosis method and artificial backward propagation neural network, which is shown to be capable of robust diagnosis of analog circuits with tolerances
Keywords :
analogue circuits; backpropagation; circuit testing; fault diagnosis; neural nets; nonlinear network analysis; tolerance analysis; ANN; analog circuits; analog fault diagnosis; artificial backward propagation neural network; component tolerances; fault diagnosis; robust diagnosis; testing time reduction; tolerances; Analog circuits; Artificial neural networks; Circuit faults; Circuit testing; Equations; Fault diagnosis; Intelligent networks; Neural networks; Neurons; Robustness;
Conference_Titel :
Signal Processing Proceedings, 2000. WCCC-ICSP 2000. 5th International Conference on
Conference_Location :
Beijing
Print_ISBN :
0-7803-5747-7
DOI :
10.1109/ICOSP.2000.893415
