论文信息 - BP neural network approach to module fault diagnosis for large analog circuit

BP neural network approach to module fault diagnosis for large analog circuit

According to circuit decomposition technology and crossover tearing technology, a fast approach of module level fault diagnosis for large analog circuit based on BP (back propagation) neural network is presented. The new approach is based on parallel diagnosis, so fault modules can be located quickly and effectively. The availability of the method is examined by simulation.

Yun Li | Yigang He | Meirong Liu

[1] Xianjue Luo,et al. A neural-based nonlinear L1-norm optimization algorithm for diagnosis of networks , 1998 .

[2] Janusz A. Starzyk,et al. A unified decomposition approach for fault location in large analog circuits , 1984 .

[3] Yichuang Sun,et al. Neural network-based L1-norm optimisation approach for fault diagnosis of nonlinear circuits with tolerance , 2001 .

[4] Yichuang Sun,et al. Fault isolation in nonlinear analog circuits with tolerance using the neural network-based L/sub 1/-norm , 2001, ISCAS 2001. The 2001 IEEE International Symposium on Circuits and Systems (Cat. No.01CH37196).

[5] Yichuang Sun,et al. A neural network approach for fault diagnosis of large-scale analogue circuits , 2002, 2002 IEEE International Symposium on Circuits and Systems. Proceedings (Cat. No.02CH37353).

[6] Cai Jin-ding. Fast Approaches of Fault Diagnosis for Large Analog Networks , 2001 .

[7] N. Navid,et al. A theory and an algorithm for analog circuit fault diagnosis , 1979 .

[8] J.W. Bandler,et al. Fault diagnosis of analog circuits , 1985, Proceedings of the IEEE.

[9] Tan Yang-hong. Neural Network Method for fault Diagnosis of Large-scale Analogue Circuits , 2001 .

[10] He Yigang,et al. A neural-based nonlinear L 1-norm optimization algorithm for diagnosis of networks , 1998 .