摘要
板料实际成形过程中摩擦润滑状态、压边力、拉延筋几何尺寸、材料特性等都具有一定的波动,都存在不确定性。传统的确定性优化设计忽略了不确定因素的影响,导致板料成形性能波动较大,产品质量水平和合格率降低。面向具有很强实用价值的多边形坯料形状优化设计问题,进一步考虑实际生产过程中的不确定因素影响。针对掌握的不确定性数据信息较少的情况,利用非线性区间数规划、函数的区间扩张、响应面代理模型技术及多目标遗传算法,构造基于区间分析的非概率稳健优化方法,并通过实际算例验证该方法的正确性和有效性。该方法大大降低了稳健优化对原始数据的要求,并降低了模具设计对设计人员经验的依赖性,提高了产品质量的稳定性,减少了废品率及生产成本。
Friction coefficient,blank holder force,drawbeads geometry and material properties in the actual process of Sheet metal forming all have a certain fluctuation,so they are uncertain.Traditional deterministic optimization design ignores uncertainties,which results in aggravating sheet metal forming performance fluctuation,reducing the product quality and qualification rate.Facing the polygon blank shape optimization problem which has a strong practical value,the uncertainties in the actual production process are further considered.Aiming at less information of uncertain data,non-linear interval number programming,function interval extension,response surface technology and multi-objective genetic algorithm are utilized to construct non-probabilistic robust optimization method based on interval analysis,and the practical examples demonstrate the validity and effectiveness of this method.This method greatly reduces the robust optimization requests for original data,reduces the mould design dependence on the designer＇s experiences,advances the stability of product quality and decreases the rejection rate and the production cost.
出处
《机械工程学报》
EI
CAS
CSCD
北大核心
2014年第10期65-71,共7页
Journal of Mechanical Engineering
基金
国家自然科学基金资助项目(51105200)
关键词
板料成形
多边形坯料
不确定
区间分析
稳健优化
sheet metal forming
polygon blank
uncertainty
interval analysis
robust optimization
