【摘要】 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更多还原

【Abstract】 In order to avoid defects in intelligent control of sheet metal deep drawing,the control technological parameter should be changed adaptively,which can be predicted from material properties and friction coefficient.An artificial neural network model for identification of material properties and friction coefficient is established according to deep drawing characteristics and more automation requirements.Real\|time identification of material properties and friction coefficient is realized with neural network,which is a new tool to process information. It lays basis of intellectualization in sheet metal deep drawing.更多还原