Hull Plate Bending Springback Prediction Based on Artificial Neural Network

Abstract:

In the process of three-dimensional curved hull plate forming, springback caused serious influence on the forming accuracy, in order to ensure the forming quality of the asymmetric multiple pressure heads CNC bending machine of ship hull 3D surface plate, to achieve the automatic processing, it is necessary to solve the problem of springback in the hull plate forming process. It is rarely to see the research on the cold bending springback problem of middle-thickness hull plate now. To established nonlinear model of plate parameters and springback amount based on BP neural network, accurately analyzing the prediction of springback, and getting the sptringback prediction model based on the BP neural network in the Matlab programming.

• Periodical: Advanced Materials Research (Volume 988)
• Pages: 309-312
• DOI: https://doi.org/10.4028/www.scientific.net/AMR.988.309
• Online since: July 2014
• Authors: Shao Juan Su*, Yong Hu, Cheng Fang Wang, Bin Liu
• Keywords: BP, Cold Forming, Numerical Simulation, Springback

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DOI: 10.1007/s12289-010-0957-z

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