TC4钛合金绿色湿式切削加工多目标参数优化

Optimization of Multi-objective Parameters for Green Wet Cutting of TC4 Titanium Alloy

为了研究在绿色湿式切削条件下各铣削参数对TC4钛合金表面粗糙度和机床周边悬浮物颗粒浓度PM2.5的影响规律,设计开展了正交铣削试验,建立了表面粗糙度和悬浮颗粒物浓度PM2.5的回归经验预测模型,在此基础上建立了基于表面粗糙度和悬浮颗粒物浓度PM2.5的多目标优化模型,进而利用NSGA-Ⅱ算法和Pareto最优理论,获得了绿色湿式切削条件下的最优铣削参数选择方案,并通过实际试验证明了该方案的可行性。

In order to study the influence of milling parameters on the surface roughness of TC4 titanium alloy and the concentration of suspended particles PM2.5 around the machine tool under the condition of green wet cutting,this paper designs and carries out orthogonal milling experiments,and establishes the regression empirical prediction model of surface roughness and suspended particulate matter concentration PM2.5.A multi-objective optimization model based on surface roughness and suspended particulate matter concentration PM2.5 is established.Furthermore,the optimal milling parameter selection scheme under the condition of green wet cutting is obtained by using NSGA-Ⅱalgorithm and Pareto optimal theory,and the feasibility of the scheme is proved by practical experiments.