摘要
为了解决目前大多数工厂对于切削参数的确定仅依靠工人个人经验或者参考手册,难以实现切削参数最优化选择的问题,文中对数控切削参数优化进行了研究,结合实际机床和道具的约束建立了一个以最大生产率及最低生产成本为优化目标的数学模型。并采用混合多目标粒子群优化算法对该数学模型进行最优化求解,其结合了多目标粒子群优化算法以及模拟退火算法,在保证了较快收敛速度的同时避免算法陷入了局部最优解。最后通过实例仿真对该模型进行验证,仿真结果显示该模型能够对数控切削参数进行优化求解。
In order to solve the problem that the majority of factories determine the optimal cutting parameters only by relying on the personal experience or reference manual of the factory for the determination of the cutting parameters,this paper studies the optimization of the numerical control cutting parameters,and combines with the constraints of the actual machine tools and establish a mathematical model with maximum productivity and minimum production cost as the optimization objective is proposed. The hybrid multi-objective particle swarm optimization algorithm is used to optimize the mathematical model. Combining the multi-objective particle swarm optimization algorithm with the simulated annealing algorithm,Fast convergence speed while avoiding the algorithm into a local optimal solution. In the end,the model is validated by example simulation. The simulation results show that the model can optimize the numerical control cutting parameters.
作者
郭婷
GUO Ting(Xi＇an Vocational and Technical College,Xi＇an 710032,China)
出处
《电子设计工程》
2018年第9期123-127,共5页
Electronic Design Engineering
关键词
数控切削
参数优化
混合多目标粒子群优化算法
模拟退火算法
NC cutting；parameter optimization；hybrid multi-objective particle swarm optimization algorithm；simulated annealing algorithm
