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Predictioln the limiting drawing ratio in Deep Drawing process by Artificial Neural Network

机译:用人工神经网络预测深加工过程中的极限拉伸比。

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In this paper back-propagation artificial neural network (BPANN) is employed to predict the limiting drawing ratio (LDR) of the deep drawing process. To prepare a training set for BPANN, some finite element simulations were carried out. die and punch radius, die arc radius, friction coefficient, thickness, yield strength of sheet and strain hardening exponent were used as the input data and the LDR as the specified output used in the training of neural network. As a result of the specified parameters, the program will be able to estimate the LDR for any new given condition. Comparing FEM and BPANN results, an acceptable correlation was found.
机译:在本文中,使用反向传播人工神经网络(BPANN)来预测深拉伸过程的极限拉伸比(LDR)。为了准备BPANN的训练集,进行了一些有限元模拟。模具和冲头半径,模具圆弧半径,摩擦系数,厚度,板材屈服强度和应变硬化指数用作输入数据,LDR用作神经网络训练中的指定输出。作为指定参数的结果,程序将能够为任何新的给定条件估算LDR。比较FEM和BPANN结果,发现可接受的相关性。

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