摘要
针对铣削加工中成本最低的优化问题,采用一种改进的人工蜂群(SP-ABC)算法对铣削参数进行优化。在基本ABC算法的基础上,嵌入粒子群(PSO)算法,以提高算法的局部寻优能力。此外,不同于传统的单工序优化,建立的优化目标模型,在考虑实际生产过程中的各种约束条件下,可同时对粗、精两个阶段多道工序同步进行优化。计算机仿真结果表明,相较其他的基本算法,该算法能够找到更优的铣削参数组合,从而实现铣削加工过程的成本最低化。
To solve the optimization problem of minimum cost in milling process,using a improved artificial bee colony algorithm to optimize the milling parameters.On the basis of the basic ABC algorithm,embedded PSO algorithm to enhance the local searching ability of the algorithm.In addition,different from the traditional single procedure optimization,the optimization target model,under considering various constraints in actual production process,can simultaneously optimize multiple processes in both phases of rough machining and finish machining.Computer simulation results show that compared with other algorithms,this algorithm can find better milling parameters combination to achieve the lowest cost of the milling process.
出处
《航空制造技术》
2016年第8期105-109,共5页
Aeronautical Manufacturing Technology
基金
江苏省产学研支撑项目(12511085)
关键词
切削参数优化
数控铣削
最低生产成本
多工序优化
人工蜂群算法
Optimization of cutting parameters
CNC milling
The lowest production cost
Multi process optimization
ABC algorithin
