基于AFSA-GA混合算法的圆锥刀轨迹优化

Conical Tool Trajectory Optimization Based on AFSA-GA Hybrid Algorithm

针对工业生产上用圆锥刀侧铣加工非可展直纹面问题,通过两点偏置法计算原始刀轴矢量位置和误差度量函数求取单刀位下的刀轴矢量位置.对于各个刀位下的不同位置优化问题,提出基于人工鱼群(AFSA)和遗传算法(GA)的混合算法作为求解策略.仿真建模计算显示,基于人工鱼群和遗传算法的混合算法的仿真计算结果精度较高,轨迹优化后刀具位置集合形成的刀具包络面误差最小,对于非可展直纹面侧铣加工具有一定的实际意义.

For the non-developable ruled surface problem of conical tool side milling in industrial production,the original tool axis vector position and error metric function are calculated by two-point offset method to obtain the tool axis vector position under the single tool position.For different position optimization problems under each cutter position,a hybrid algorithm based on artificial fish swarm (AFSA) and genetic algorithm (GA) is proposed as the solution strategy.Simulation modeling calculation shows that the simulation results of hybrid algorithm based on AFSA-GA are accurate,and the tool envelope surface error formed by the tool position set after trajectory optimization is the smallest,which has certain practical significance for non-expandable straight expandable side milling machining.