A Fault Diagnosis Expert System Base on Artificial Neural Network for Mixed-Signal Circuits
This paper investigates a fault diagnosis expert system base on artificial neural network (ANN-FD-ES) for mixed-signal circuits. We built this system by given a faulty circuit. Based on the transient response testing (TRT) on the mixed-signal circuits, both analog and digital signal characteristics are unified. The system includes knowledge base,reasoning machine, explanatory, and interface. The diagnostic portion of the system is based on neural-calculation approach, which is used to establish the knowledge base composed of the weigh values and threshold values. With this approach, conclusions are developed directly from the outputs of the net, rather than the domain knowledge in traditional expert system. Compared with the traditional expert system, this system is good at processing data. The experimental results show that the system not only improves the shortcoming of the traditional expert system such as the deficiency on knowledge acquisition and self-learning capability, but also achieves a satisfied fault diagnosis efficiency.
ANNES mixed-signal circuits transient response testing fault diagnosis ES
Li Chunming Hu Dawei
Inner Mongolia University of Technology,College of Information Engineering,Huhhot 010051 China
国际会议
西安
英文
2007-08-16（万方平台首次上网日期，不代表论文的发表时间）