DocumentCode
684981
Title
Fault diagnosis of hydraulic system based on improved BP neural network technology
Author
Zhang Yinshuo ; Xia Jun ; Li Lei
Author_Institution
No.3 Dept., Nanjing Artillery Acad., Langfang, China
Volume
01
fYear
2013
fDate
16-18 Aug. 2013
Firstpage
137
Lastpage
140
Abstract
A fault diagnosis model with BP network for a certain hydraulic system were described. The realization process of the fault diagnosis based on the improved BP algorithm was discussed. According to the experiment, the improved BP network has better learning ability, higher convergence rate ability and higher stability of learning and memory. The diagnosis results indicate that the presented diagnosis method has higher reliability and can attain the expected results, which can be applied to fault diagnosis of hydraulic system.
Keywords
backpropagation; fault diagnosis; hydraulic systems; mechanical engineering computing; neural nets; BP neural network technology; convergence rate ability; fault diagnosis; hydraulic system; learning ability; learning stability; memory stability; Artificial intelligence; Biological neural networks; Fault diagnosis; Hydraulic systems; Mathematical model; Neurons; BP algorithm; fault diagnosis; hydraulic system; neural network;
fLanguage
English
Publisher
ieee
Conference_Titel
Measurement, Information and Control (ICMIC), 2013 International Conference on
Conference_Location
Harbin
Print_ISBN
978-1-4799-1390-9
Type
conf
DOI
10.1109/MIC.2013.6757933
Filename
6757933
Link To Document