Prediction of Spring Back of the Two-Axle Rotary Shaping Based on Neural Network

Abstract:

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Two-axle rotary shaping is one of advanced sheet metal forming process that combined stamping ascendant used elastic medium with traditional rotary shaping principle. The prediction model of two-axle rotary shaping is set up to predict the springback for two-axle rotary shaping. It used the back propagation neural network because of the better nonlinear mapping ability. Some of data from the experiment and FEM simulation is applied to train the network; the other data is used to test the prediction result. The result showed that the value of prediction and experiment is in good agreement, and just small error is existed. It demonstrated that the neural network model might predict the springback of two-axle rotary shaping and reduce the number of simulation calculation and experiment operation. It can offer a powerful guidance for rapid choice of process parameters in production.

Info:

Periodical:

Materials Science Forum (Volumes 532-533)

Edited by:

Chengyu Jiang, Geng Liu, Dinghua Zhang and Xipeng Xu

Pages:

1044-1047

DOI:

10.4028/www.scientific.net/MSF.532-533.1044

Citation:

S. H. Lu and J. Wang, "Prediction of Spring Back of the Two-Axle Rotary Shaping Based on Neural Network", Materials Science Forum, Vols. 532-533, pp. 1044-1047, 2006

Online since:

December 2006

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Price:

$35.00

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