Title :
Expert system of fault diagnosis based on the neural network and regulations
Author :
Shu, Cheng ; Qinhe, Gao ; Junjun, Yu
Author_Institution :
Second Artillery Eng. Coll., Shannxi, China
Abstract :
After pointing out the limitations of expert system and neural network respectively, this article gives a model of fault diagnostic expert system which unifies the neural network and production rules. It also improves the BP neural network model and drives a global optimum algorithm that improves the ability of network. Practical applications prove that this method can solve the fault diagnostic problem of multi-fault and multi-procedure complicated mechanical devices
Keywords :
backpropagation; diagnostic expert systems; fault diagnosis; neural nets; backpropagation; diagnostic expert system; fault diagnosis; global optimum algorithm; neural network; Artificial intelligence; Artificial neural networks; Backpropagation; Diagnostic expert systems; Expert systems; Fault diagnosis; Feeds; Neural networks; Pattern recognition; Production systems;
Conference_Titel :
Intelligent Control and Automation, 2000. Proceedings of the 3rd World Congress on
Conference_Location :
Hefei
Print_ISBN :
0-7803-5995-X
DOI :
10.1109/WCICA.2000.859976