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| Strip Crown Prediction of Cold Strip Rolling Based on FEM-ANN |
| DU Feng-shan1,2,XUE Tao1,2,WANG Chao1,2,YU Feng-qin1,2,SUN Jing-na1,2 |
1. School of Mechanical Engineering, Yanshan University, Qinhuangdao 066004, Hebei, China
2. National Engineering Research Center for Equipment and Technology of Cold Strip Rolling,Yanshan University, Qinhuangdao 066004, Hebei, China |
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Abstract Using nonlinear elastic-plastic finite element method, a 3D FE simulation model of 1450 HC rolling process was developed with the nonlinear FE software MSC.Marc. Based on the model, a large amount of models which contain different rolling parameters was simulated and the strip crown was obtained. The effects of different rolling parameters, strip and rollers parameters on the strip crown were investigated and the main rules were mastered. The simulation results of the strip crown are served as the sample database of BP neural network by which the prediction model of cold rolled strip crown was built. During the training, an improved arithmetic was used in the BP neural network. Practice had proved: an improved arithmetic of BP neural networks improves the speed of learning and builds up the feasibility of arithmetic. The problem that the finite element method is time consuming and difficult to be used to the online flatness control is solved, and the precision of flatness online control is enhanced by this method.
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Received: 22 January 2013
Published: 19 August 2013
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2013, Vol. 48 
