基于模糊粗糙集理论的模具数控切削参数优化

在分析模具数控切削加工特点的基础上，提出了切削参数的优化模型．根据实际加工中积累的数据，构造了切削参数与其影响因素的决策表，并对决策表中的属性值进行分析和处理，将语义型属性值转化为离散值，区间属性值转化为模糊区间数．提出了基于模糊相似关系的粗糙集理论规则学习算法，并将其用于优化变量约束范围的规则提取，给出了在一定表面粗糙度范围内切削参数的约束范围．最后，应用遗传算法求解切削参数的最优值．

Optimization of Cutting Parameters for Mold NC Machining Based on Fuzzy and Rough Set Theory

Based on the analysis of the property of mold NC manufacturing an optimization model of cutting parameters was presented. The decision table of milling parameters collected from the practice machining operation was constructed to obtain the range of optimization parameters. The values of nominal attribute and interval attribute in the decision table were respectively transformed into crisp values and fuzzy interval valued numbers. The algorithm of rules induction for the decision of containing range of milling parameters was introduced based on fuzzy similarity rough set. At last, the application of genetic algorithm to optimization solution was described.