Title :
Application of BP Neural Network in the Control of Hydraulic Die Forging Hammer
Author :
Yan, Li ; Jianwei, Li ; Jun, Liu
Author_Institution :
Mech. & Electr. Eng. Coll., Henan Agric. Univ., Zhengzhou, China
Abstract :
It is an essential problem in the control of hydraulic die forging hammer that the mathematical model between deformation and forging energy, and it is nonlinear in nature. For its pretty nonlinear function approximation ability, BP neural network is suitable for resolving the problem. The architecture and the arithmetic of BP neural network were introduced. Furthermore, the BP neural network model was established. At the same time, the process and principle of the modeling also were expounded. Then, it was explained that how to use the BP neural network model in the control process. The result of experiment showed that the method takes effect very well. Other applications of BP neural network in the control of hydraulic die forging hammer was also introduced. At last, the disadvantage of the method was discussed briefly.
Keywords :
backpropagation; forging; hammers (machines); hydraulic systems; neurocontrollers; nonlinear functions; BP neural network; deformation; forging energy; hydraulic die forging hammer control; nonlinear function approximation; Adaptive control; Arithmetic; Automatic control; Energy resolution; Feeds; Function approximation; Mathematical model; Neural networks; Neurons; Size control; BP Neural Network; Hydraulic Die Forging Hammer; forging energy;
Conference_Titel :
Intelligent Computation Technology and Automation, 2009. ICICTA '09. Second International Conference on
Conference_Location :
Changsha, Hunan
Print_ISBN :
978-0-7695-3804-4
DOI :
10.1109/ICICTA.2009.17