DocumentCode
3161662
Title
Fault diagnosis of 40TM liquid-gas hammer based on BP algorithm: Artificial Neural Network
Author
Xie, Miao ; Chang, Sheng ; Mao, Jun ; Li, Kangkang ; Wan, Zhuo
Author_Institution
Coll. of Mech. Eng., Liaoning Tech. Univ., Fuxin, China
fYear
2011
fDate
16-18 April 2011
Firstpage
4964
Lastpage
4967
Abstract
The basic principle of Artificial Neural Networks and BP algorithm was introduced in this paper. The application of BP algorithm Artificial Neural Networks in fault diagnosis of 40TM liquid-gas hammer was studied. The superiority of BP algorithm Artificial Neural Networks in fault diagnosis was proved by the MATLAB simulation and the training. The causes of faults were determined by BP algorithm Artificial Neural Networks.
Keywords
backpropagation; fault diagnosis; forging; neural nets; production engineering computing; 40TM liquid-gas hammer; BP algorithm; artificial neural network; fault diagnosis; Artificial neural networks; Atmospheric modeling; Fault diagnosis; Fuels; Mathematical model; Training; Valves; 40TM liquid-gas hammer; BP algorithm; Fault diagnosis;
fLanguage
English
Publisher
ieee
Conference_Titel
Consumer Electronics, Communications and Networks (CECNet), 2011 International Conference on
Conference_Location
XianNing
Print_ISBN
978-1-61284-458-9
Type
conf
DOI
10.1109/CECNET.2011.5768925
Filename
5768925
Link To Document