神经网络在毛坯形状预测中的应用

Application of Blank Profile Predication Based on Neural Network

从影响冲压成型结果的因素和有限元网络映射法反算毛坯形状的方法出发,提出了基于神经网络预测毛坯形状模型的方法。选取凸模圆角半径、凹模圆角半径、压边力和摩擦系数等作为影响冲压成型结果的因素,利用正交表和随机法产生径向基神经网络的学习样本,用有限元网络映射法反算的毛坯的长度作为神经网络的输出,通过影响冲压成型结果因素的随机样本对神经网络进行检测。实验表明,提出了预测毛坯形状模型的方法是有效的。

A method of predicating the blank profile based on neural network is put forward according to the influencing factors of press forming results and means of back calculating blank profile by finite element network mapping technique. In this method, the punch （profile） and, die profile radius, blank holder force and friction coefficient are taken as the influencing factors of the press forming results and the sample for learning radial basis function neural network is generated with orthogonal array and randomized method. The length of blank profile which is back calculated by the means of finite element network mapping technique is used as the output of neural network and it is detected through random sampling. The experiment indicates that the method proposed in this paper is effective.