摘要
针对车顶盖大曲率半径件成形切边后回弹大的问题,在有限元数值模拟的基础上建立了以工件回弹前后对应节点偏差为目标函数,以成形中的压边力和分段拉延筋力为变量的工艺优化模型,通过径向基函数神经网络和模拟退火算法对其进行了优化求解。结果表明,建立的优化模型是合理的,采用优化后的工艺参数进行冲压成形后在保证产品不产生破裂和起皱的前提下能够显著减少工件的回弹量。
Aimed at reducing the springback after trimming for large curvature radius auto-roof panel,an optimization model was established based on finite element simulation,with the deviation of corresponding nodes for the panel before and after springback as objective function,blank holder force and draw bead force as variable.To solve the model,radial basis function neural networks（ANN） method and simulated annealing（SA） algorithm were employed.Results show that the proposed optimization model is feasible,and springback magnitude of the panel would be reduced obviously when forming with the optimized process parameters,while no such defects as wrinkle and fracture occur.
出处
《锻压技术》
CAS
CSCD
北大核心
2011年第3期144-147,共4页
Forging & Stamping Technology
基金
广州市科技计划项目(2007Z2-D9031)
广东省教育厅广东高校优秀青年创新人才培育资助项目(育苗工程项目)(wym09110)
关键词
回弹
优化模型
板料冲压
成形工艺
springback
optimization mudel
sheet metal stamping
forming process
