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- W2385599056 abstract "BP artificial neural network and FEM simulation were applied to optimize the design for the prediction of springback value in the stamping process based on MATLAB.A three-layer neural network was used to set up mathematical model for springback prediction based on variable pressure-pad-forces.Orthogonal test was arranged for numerical simulation to get Z-displacement at the endpoint,which was used as the target value of the model.The neural network was trained by the above Z-displacement values to form knowledge source,and the general optimal solution was attained through genetic algorithm.Nonlinear relationship between stamping process parameters and quantity of springback was obtained through the neural network,whose accuracy was testified by the test samples.The work performed in this paper shows that the combination of network,orthogonal test and numerical simulation may obviously reduce the time of optimizing process parameters and improve the process design efficiency.At the same time,on condition that the time of numerical simulation is available,the more precise conclusion can be obtained." @default.
- W2385599056 created "2016-06-24" @default.
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- W2385599056 date "2007-01-01" @default.
- W2385599056 modified "2023-09-25" @default.
- W2385599056 title "Prediction of Springback Value for U Shaped Parts in the Stamping Process of Auto Body Panel Based on BP Neural Network" @default.
- W2385599056 hasPublicationYear "2007" @default.
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