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在板材拉深成形智能化控制过程中 ,为了避免缺陷的产生 ,必须适时地改变控制工艺参数 ,而最佳控制参数要根据材料的性能参数和摩擦系数来预测。根据拉深成形过程的特点及生产过程中自动化程度的要求 ,建立了材料性能参数和摩擦系数识别的人工神经网络模型。利用神经网络这种新一代信息处理工具实现了材料性能参数和摩擦系数的实时识别 ,为实现板材拉深成形过程的智能化控制奠定了基础
In the process of intelligent control of sheet metal forming, in order to avoid defects, the control process parameters must be changed timely, and the optimal control parameters should be predicted according to the material performance parameters and friction coefficient. According to the characteristics of the deep drawing process and the degree of automation in the production process, an artificial neural network model of material performance parameters and friction coefficient identification was established. The new generation of information processing tools, such as neural network, realizes real-time identification of material performance parameters and friction coefficient, which lays the foundation for realizing intelligent control of sheet metal forming process.