Prediction of Springback of the One-Axle Rotary Shaping Based on Artificial Neural Network

Abstract:

One-axle rotary shaping with the elastic medium (RSEM) is a kind of advanced sheet metal forming process. The research object is the springback of aluminous U-section. The orthogonal method is used to arrange the simulation experiments, the forming and springback of the workpiece are simulated successfully with the Finite Element Simulation software, and The main factors influenced the RSEM are analyzed. The simulation results are used as the training samples of the artificial neural network (ANN), and the ANN prediction model of RSEM process is set up. The prediction results would be tested with the experiment data, and only a little tolerance was existed between the two values. It demonstrated that the combination of orthogonal test, numerical simulation and neural network could effectively predict the springback of RSEM, the design efficiency of process parameters would be improved. It would guide the development of precision forming technology.

• Periodical: Key Engineering Materials (Volumes 535-536)
• Pages: 318-321
• DOI: https://doi.org/10.4028/www.scientific.net/KEM.535-536.318
• Online since: January 2013
• Authors: Xia Jin, Shi Hong Lu
• Keywords: Finite Element (FE) Simulation, Neural Network (NN), One-Axle Rotary Shaping, Prediction, Springback

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