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对钛合金材料Ti6Al4V铣削加工进行有限元数值计算,结合试验设计方法构建了基于支持向量回归机(SVR)的铣削力预测模型,以材料去除率和刀具寿命为优化目标,提出一种基于支持向量回归机和带精英策略的非支配排序遗传算法(NSGA-Ⅱ)的优化方法。结果表明,该方法能够获得满意的Pareto解集,为钛合金铣削参数优化提供一种新的方法,具有良好的推广价值。
The Ti6Al4V milling titanium alloy material is calculated by finite element method. Combined with the experimental design method, the milling force prediction model based on Support Vector Regression (SVR) is constructed. Taking the material removal rate and tool life as optimization targets, Regression machine and the optimization method of non-dominated ranking genetic algorithm (NSGA-Ⅱ) with elite strategy. The results show that this method can obtain a satisfactory Pareto solution set and provide a new method for milling parameters optimization of titanium alloy with good promotion value.