DocumentCode :
2294123
Title :
Researches and application of a hybrid fault diagnosis expert system
Author :
Zhang, Dinghui ; Dai, Shuguang ; Zheng, Youqin ; Zhang, Renjie ; Mu, Ping an
Author_Institution :
Coll. of Opt. & Electron. Inf. Eng., Univ. of Shanghai for Sci & Technol., China
Volume :
1
fYear :
2000
fDate :
2000
Firstpage :
215
Abstract :
It is difficult to use a single diagnosis theory or method to monitor and diagnose the whole condition of a large complicated system. To realize real-time condition monitoring and fault diagnosis of a large automatic production line in a steel factory, according to the structure and fault diagnosis characteristics of the production line system, a hybrid fault diagnosis expert system based on knowledge and neural network has been researched and built. This paper introduces the basic composition of the hybrid expert system, and gives the rule examples of the expert system based on knowledge, and emphatically introduces knowledge expression and knowledge acquisition and fault diagnosis inference of the fault diagnosis expert system based on neural network. Finally, fault diagnosis examples based on neural network are given. Research results show that a hybrid expert system is very effective to monitor and diagnose a large complicated modern production process
Keywords :
condition monitoring; diagnostic expert systems; inference mechanisms; knowledge acquisition; manufacturing data processing; neural nets; real-time systems; condition monitoring; diagnostic expert system; fault diagnosis; hybrid expert system; inference; knowledge acquisition; neural network; production line; steel factory; Computerized monitoring; Condition monitoring; Diagnostic expert systems; Fault diagnosis; Neural networks; Process control; Production facilities; Production systems; Real time systems; Steel;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Intelligent Control and Automation, 2000. Proceedings of the 3rd World Congress on
Conference_Location :
Hefei
Print_ISBN :
0-7803-5995-X
Type :
conf
DOI :
10.1109/WCICA.2000.859951
Filename :
859951
Link To Document :
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