DocumentCode :
3600095
Title :
Study of Rotating Machinery Fault Diagnosis Model with Integrating Neural Network and Expert System
Author :
Wang, Yanqiu ; Yang, Kejian
Author_Institution :
Coll. of Electr. Eng., Liaoning Univ. of Technol., Jinzhou, China
Volume :
2
fYear :
2009
Firstpage :
9
Lastpage :
13
Abstract :
Aimed at these shorts of the unity expert system in rotate machine fault diagnosis, a new method of neural network interfused with traditional expert system is presented in rotate machine fault diagnosis. The frame and function expression of rotate machine fault diagnosis system based on neural network and traditional expert system are given. The select method of diagnosis parameter and the setting up process of knowledge database and module of neural network are analyzed. The experiment results demonstrate that diagnosis faults method is effective.
Keywords :
electric machines; expert systems; fault diagnosis; mechanical engineering computing; neural nets; expert system; knowledge database; neural network; rotating machinery fault diagnosis; Artificial neural networks; Diagnostic expert systems; Educational institutions; Expert systems; Explosions; Fault diagnosis; Knowledge acquisition; Logic; Machinery; Neural networks; Expert System; Fault Diagnosis; Neural Network; Rotate Machine;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Hybrid Intelligent Systems, 2009. HIS '09. Ninth International Conference on
Print_ISBN :
978-0-7695-3745-0
Type :
conf
DOI :
10.1109/HIS.2009.114
Filename :
5254410
Link To Document :
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