DocumentCode :
1589678
Title :
Fault Detection of Oil Pump Based on Fuzzy Neural Network
Author :
Tian, Jingwen ; Gao, Meijuan ; Cao, Liting ; Li, Kai
Author_Institution :
Beijing Union Univ., Beijing
Volume :
2
fYear :
2007
Firstpage :
636
Lastpage :
640
Abstract :
Considering the issues that the relationship between the fault of oil pump existent and fault information is a complicated and nonlinear system, and it is very difficult to found the process model to describe it. The fuzzy neural network has the advantages of both fuzzy theory and neural network. In this paper, a fault detection method of oil pump based on fuzzy neural network is presented, moreover, we construct the structure of fuzzy neural network that used for the fault detection of oil pump, and adopt the Levenberg-Marquart optimizing algorithm to train fuzzy neural network. With the ability of strong self-learning and function approach of fuzzy neural network, the detection method can truly diagnosticate the fault of oil pump by learning the fault information of oil pump. The real detection results show that this method is feasible and effective.
Keywords :
fault diagnosis; fuel pumps; fuzzy neural nets; mechanical engineering computing; Levenberg-Marquart optimizing algorithm; fault detection method; fault information; fuzzy neural network; fuzzy theory; nonlinear system; oil pump; Artificial neural networks; Costs; Fault detection; Fuzzy control; Fuzzy neural networks; Fuzzy systems; Neural networks; Neurons; Nonlinear systems; Petroleum;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Natural Computation, 2007. ICNC 2007. Third International Conference on
Conference_Location :
Haikou
Print_ISBN :
978-0-7695-2875-5
Type :
conf
DOI :
10.1109/ICNC.2007.375
Filename :
4344428
Link To Document :
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