韩军, 姚晟. SA-PSO混合算法的侧铣刀轴轨迹规划[J]. 制造技术与机床, 2022, (6): 92-99. DOI: 10.19287/j.mtmt.1005-2402.2022.06.015
引用本文: 韩军, 姚晟. SA-PSO混合算法的侧铣刀轴轨迹规划[J]. 制造技术与机床, 2022, (6): 92-99. DOI: 10.19287/j.mtmt.1005-2402.2022.06.015
HAN Jun, YAO Sheng. Tool axis trajectory planning for flank milling based on SA-PSO hybrid algorithm[J]. Manufacturing Technology & Machine Tool, 2022, (6): 92-99. DOI: 10.19287/j.mtmt.1005-2402.2022.06.015
Citation: HAN Jun, YAO Sheng. Tool axis trajectory planning for flank milling based on SA-PSO hybrid algorithm[J]. Manufacturing Technology & Machine Tool, 2022, (6): 92-99. DOI: 10.19287/j.mtmt.1005-2402.2022.06.015

SA-PSO混合算法的侧铣刀轴轨迹规划

Tool axis trajectory planning for flank milling based on SA-PSO hybrid algorithm

  • 摘要: 针对非可展直纹面的原理性误差问题,采用单个刀轴位置的误差判定函数作为目标函数,即单个刀轴上的各点到非可展直纹面的距离减去刀轴半径的平方最小。在MATLAB中利用SA-PSO(模拟退火算法和粒子群算法)混合算法对其进行求解,该混合算法解决了单刀位情况下刀轴最优位置的寻求问题。通过对比PSO算法和SA-PSO算法包络误差的极差值均值表明:SA-PSO混合算法欠切和过切误差对比于单一的粒子群算法减少了14.7%,实际加工并检测叶片精加工的表面误差验证了方法的可行性。

     

    Abstract: Aiming at the problem of principle error of non-developable ruled surface, the error determination function of single tool axis position is proposed as the objective function, that is, the distance from each point on a single tool axis to the non-developable straight surface minus the square of the tool axis radius is minimum. In MATLAB, the SA-PSO (simulated annealing algorithm and particle swarm optimization) hybrid algorithm is used to solve it. The hybrid algorithm solves the problem of finding the optimal position of tool axis in the case of single tool position. By comparing the envelope errors of PSO algorithm and SA-PSO algorithm, it is shown that the undercutting and overcutting errors of SA-PSO hybrid algorithm are 14.7% less than the single particle swarm optimization algorithm. The feasibility of the method is verified by actual machining and surface error detection of blade finishing.

     

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