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
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;
Conference_Titel :
Consumer Electronics, Communications and Networks (CECNet), 2011 International Conference on
Conference_Location :
XianNing
Print_ISBN :
978-1-61284-458-9
DOI :
10.1109/CECNET.2011.5768925
