计算机集成制造系统 ›› 2022, Vol. 28 ›› Issue (2): 507-517.DOI: 10.13196/j.cims.2022.02.015

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基于遗传算法的多主轴头加工空行程轨迹规划#br#

崔榕芳1,陈蔚芳1+,潘立剑1,朱帅2,刘振华2   

  1. 1.南京航空航天大学机电学院
    2.江苏中智自动化有限公司
  • 出版日期:2022-02-28 发布日期:2022-03-11
  • 基金资助:
    国家自然科学基金资助项目(51775277);泰州市科技支撑计划资助项目(TG201912)。

Trajectory planning for empty run of multi-spindle processing based on genetic algorithm

  • Online:2022-02-28 Published:2022-03-11
  • Supported by:
    Project supported by the National Natural Science Foundation,China (No.51775277),and the Taizhou Science and Technology Supporting Plan,China(No.TG201912).

摘要: 针对多主轴头五轴机床加工时需手动规划空行程的问题,提出一种空行程轨迹自动规划方法。在机床运动学建模的基础上,针对刀位点轨迹和刀轴矢量,分别提出基于最短路径的刀位点轨迹规划和无碰撞刀轴矢量规划,将空行程规划问题转化为参数优化问题。为了简化碰撞检测,提出两级相交检测算法。通过加权系数法建立空行程规划的目标函数,并采用遗传算法求解,规划出一条无碰撞、运动时间最短、旋转轴角度变化量最小、末端轨迹最短的具有柔性的理想轨迹。在Vericut建立的仿真平台上,验证了该方法的可行性和有效性。所提方法具有拓展性,通过多次分解轨迹求取棱交点能够实现复杂工件的空行程规划。

关键词: 轨迹规划, 无干涉, 多主轴头加工, 遗传算法, 最短路径

Abstract: Aiming at the need to manually plan empty run during multi-spindle 5-axis processing,an automatic empty run trajectory planning method was put forward.On the basis of multi-spindle machine tool kinematics modeling,aiming at the cutter location point trajectory and generating of tool axis vector,the cutter location point trajectory based on shortest path and collision-free tool axis vector planning were proposed respectively,so that the empty run planning was converted into a parameter-optimization problem.To simplify collision detection,a two-level intersection detection algorithm was proposed.The objective function of empty run planning was established by weighting coefficient method,and it was solved by genetic algorithm,so that a flexible ideal trajectory with no collision,shortest movement time,smallest change of rotation axis angle and shortest ending-trajectory was planned.In the simulation platform established by Vericut,the feasibility and effectiveness of the method had been verified.The empty-run trajectory planning for complex work-piece could be realized by decomposing trajectories and calculating intersections with work-piece edge for many times.

Key words: trajectory planning, non-interference, multi-spindle processing, genetic algorithms, shortest path

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