四主轴头五轴机床多工步加工路径优化

Multi-step machining path optimization of five-axis machine tool with four-spindle heads

针对四主轴头多工步加工空行程耗时多的问题,基于空行程路径最短原则研究了无碰撞多工步加工路径优化方法。以四主轴头机床为对象确定了关节坐标系,在单面加工空行程规划基础上,建立了多面空行程计算模型和防碰撞多工步路径优化模型。基于同一面优先排序原则,在内层混合粒子群算法(GA-PSO)基础上融合了贪心算法,提出了双层混合粒子群优化算法(GA-PSO)。其中内层算法用于优化单一面上路径轨迹,外层算法用于优化多面间加工顺序。通过内外层优化算法间的不断迭代分层优化空行程,实现了整体多工步路径优化。对双层GA-PSO算法进行了算例分析,与遗传算法相比具有更快的收敛速度和更短的加工路径,最后通过虚拟仿真进一步验证了该路径优化算法的可行性。

Aiming at the time-consuming problem of four-spindle heads and multi-step machining empty stroke,based on the principle of the shortest empty stroke path,a collision-free multi-step machining path optimization method was studied.A four-spindle-head machine tool was used as the object to determine the joint coordinate system.Based on the single-sided machining empty stroke planning,a multi-faceted empty stroke calculation model and an anti-collision multi-step path optimization model were established.Based on the principle of priority ordering on the same side,the greedy algorithm was integrated on the basis of the inner GA-PSO algorithm,and a two-layer GA-PSO optimization algorithm was proposed.The inner layer algorithm was used to optimize the path trajectory on a single surface,and the outer layer algorithm was used to optimize the processing sequence between multiple surfaces.Through the continuous iteration between the inner and outer layer optimization algorithms to optimize the idle stroke layer by layer,the overall multi-step path optimization was realized.A case study of the double-layer GA-PSO algorithm was carried out.Compared with the genetic algorithm,it had a faster convergence speed and a shorter processing path.Finally,the feasibility of the path optimization algorithm was further verified by virtual simulation.