基于Kriging-MIGA算法的薄壁件铣削参数优化

Optimization of milling parameters of thin-walled parts based on Kriging-MIGA algorithm

针对某铝合金薄壁壳零件的加工变形问题,以铣削力为优化目标,通过Isight平台,提出了基于Kriging-MIGA算法的铣削参数优化方法。采用了最优拉丁超立方试验设计方法建立参数样本点,利用样本点搭建铣削参数与铣削力间的Kriging近似模型,采用了MIGA算法对近似模型全局优化,获取1组能够使铣削力最小的铣削参数组合并得出预测值。研究结果表明:基于Kriging-MIGA算法的铣削参数优化,使得铣削力降低了39.37%,有效减小了铝合金薄壁壳的变形量。该研究方法对薄壁件铣削参数选值具有重要的意义。

Aiming at the machining deformation problem of an aluminum alloy thin-walled shell part, with the milling force as the optimization goal, through the Isight platform, a milling parameter optimization method based on the Kriging-MIGA algorithm is proposed. The optimal Latin hypercube experimental design method was used to establish the parameter sample points, and the Kriging approximate model between the milling parameters and the milling force was built using the sample points. The MIGA algorithm was used to globally optimize the approximate model, and a set of milling that could minimize the milling force was obtained. Combine the parameters and get the predicted value. The research results show that the optimization of milling parameters based on the Kriging-MIGA algorithm reduces the milling force by 39.37% and effectively reduces the deformation of the aluminum alloy thinwalled shell. The research method in this paper is of great significance to the selection of milling parameters of thin-walled parts.