基于粒子群算法的数控加工切削参数优化

Computer Numerical Control Machining Parameter Optimization Based on Particle Swarm Optimization

以实际生产加工中的经验公式为基础,考虑加工中机床和刀具的实际约束,建立了以进给量和切削速度为变量,以最大生产率和最低生产成本为优化目标的多目标优化模型,并引入协调系数将其转化成单目标优化模型.应用粒子群算法对数学模型进行寻优求解.实例表明经过优化计算得到的切削参数取值比经验值更能满足优化目标,也说明了粒子群算法适用于解决复杂的非线性优化问题.

Based on the empirical formula from the practical producing process, a multi-objective optimizing model is established by taking constraints of lathe and cutting tool into consideration. Some cutting parameters such as feed and cutting velocity are taken as variables in the model. And the model aims at both peak performance and lowest cost. A concerted coefficient is adopted to convert the multi- objective model into a single-objective model. Based on the model, the optimal cutting parameters are generated with particle swarm optimization （PSO）. An example shows that the optimal cutting parameters are easier to satisfy the optimizing object than the empirical ones,and PSO is applicable for solving complicated nonlinear problem.