基于遗传算法的铣削参数优化

Optimization of Process Parameters for Milling Operations Using Genetic Algorithm

为了科学选取铣削用量,提高生产效率、降低生产成本。利用试验数据建立参数的回归方程,采用线性回归方法推导出经验公式。建立了以铣削加工参数为设计变量,以铣削力、机床有效功率、零件表面粗糙度等为约束条件,以加工时间和成本为目标的优化函数。在传统遗传算法的基础上,改进了编码方式和适应度函数,对铣削参数进行优选。试验表明,该方法具有较好的实用性和有效性。

To improve productivity and reduce costs, it is very important to choose milling parameters scientifically. The regression equation of the parameters was established with the test data, and the em- pirical formula was deduced by means of linear regression analysis. Taking the establishment of the mill- ing processing parameters as the design variables, optimization functions were constructed with the mill- ing force, machine effective power and surface roughness as the nonlinear constrained conditions. The goal of the function is to get the minimum processing time and production cost. The traditional genetic algorithm was improved in the aspect of the coding method and fitness function to optimize the milling parameters. The experiment proved that the method has well practicability and effectiveness.