摘要
针对轮毂锻模的上模芯磨损剧烈的问题,将锻造成形数值模拟、BP神经网络和SQP算法耦合以优化模具的型面,改善上模芯的磨损情况,从而提高模具的寿命。基于MATLAB平台,以等磨损为目标建立优化数学模型,采用3次样条插值曲线描述上模芯成形部位的轮廓形状。结合锻造成形数值模拟和修正的Archard磨损模型得到计算结果并以此训练BP神经网络,建立模具型腔控制点与目标函数之间的映射关系。运用SQP算法对设计变量进行寻优,得到最优的上模芯成型部位的轮廓形状,并对此轮廓的磨损情况进行数值模拟验证。结果表明:优化后成形上模芯磨损量减小且更加均匀,等磨损值下降了38.4%。
A method combining forging numerical simulation, BP neural network and SQP algorithm is developed to optimize the die cavity and reduce the wear of top die core, so as to improve die life. Optimal mathematical model is established for the purpose of equal wear and cubic spline interpolation curve is used to describe the shape of the forming part of top die core based on MATLAB. Then BP neural network is trained by the results of forging numerical simulation and modified Archard wear model to establish the relation between the control point of die cavity and the objective function. Finally,SQP algorithm is used to optimize the design variables and get the best shape of top die core. The results show that the wear of top die core decreases and becomes more uniform. The uniformity wear is reduced by 38.4% after optimization.
出处
《重庆大学学报（自然科学版）》
EI
CAS
CSCD
北大核心
2014年第3期16-22,共7页
Journal of Chongqing University
基金
中央高校基本科研业务费资助项目(CDJZR13130087)
国家自然科学基金青年基金项目(51205427)
科技重大专项资助项目(2012ZX04010-081)
