河北水利电力学院学报

河北水利电力学院学报 ›› 2022, Vol. 32 ›› Issue (3): 70-75.DOI: 10.16046/j.cnki.issn2096-5680.2022.03.011

• 机械工程专题 • 上一篇    下一篇

利用蚁群算法求解机械加工路径规划问题

张鹏程, 王文成, 宫翔, 贾新立   

  1. 1.河北省工业机械手控制与可靠性技术创新中心,河北省沧州市黄河西路49号 061001;
    2.沧州市工业机械手控制与可靠性技术创新中心,河北省沧州市黄河西路49号 061001;
    3.河北水利电力学院机械工程系,河北省沧州市黄河西路49号 061001;
    4.河北水利电力学院电力工程系,河北省沧州市黄河西路49号 061001
  • 收稿日期:2022-04-14 修回日期:2022-07-12 出版日期:2022-09-30 发布日期:2023-10-26
  • 作者简介:张鹏程(1976-),男,河北泊头人,硕士,高级实验师,研究方向为计算机辅助设计、智能布局。E-mail:zpc-rjy@163.com
  • 基金资助:
    河北省教育厅科学技术研究项目资助(ZD2022081);河北省教育厅科学技术研究项目资助(ZD2021329)沧州市科技计划自筹经费项目(213101014);沧州市科技计划自筹经费项目(204108009)

Solving Machining Path Planning Problem by Ant Colony Algorithm

ZHANG Peng-cheng1,2,3, WANG Wen-cheng1,2,3, GONG Xiang1,2,3, JIA Xin-li1,2,4   

  1. 1. Industrial Manipulator Control and Reliability Technology Innovation Center of Hebei, 061001, Cangzhou, Hebei, China;
    2. Industrial Manipulator Control and Reliability Technology Innovation Center of Cangzhou, 061001, Cangzhou, Hebei, China;
    3. Department of Mechanical Engineering, Hebei University of Water Resources and Electric Engineering, 061001, Cangzhou, Hebei, China;
    4. Department of Electrical Engineering, Hebei University of Water Resources and Electric Engineering, 061001, Cangzhou, Hebei, China
  • Received:2022-04-14 Revised:2022-07-12 Online:2022-09-30 Published:2023-10-26

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摘要： 针对机械加工中孔群加工刀具路径规划问题,采用蚁群算法,通过多目标搜索和并行计算,快速从众多可行加工路线中找到一条最短路径作为刀具运动的轨迹,该路径可以最大限度的节省加工过程中的空行程时间,提高整体加工效率。采用控制变量法和正交试验法,结合算例,分析研究算法实现过程中需优化取值的蚂蚁的数量、信息素重要程度因子、启发函数重要程度因子、信息素挥发因子、总信息量等5个重要参数对于最优解质量的影响,探究其作用规律,为进一步提高算法优化结果和改进算法提供参考依据。

关键词: 蚁群算法, 路径规划, 孔群, TSP问题, 正交试验法

Abstract: Aiming at the problem of tool path planning for hole group machining in mechanical processing, ant colony algorithm is used. Through multi-objective search and parallel computing, a shortest path is quickly found from many feasible machining routes as the trajectory of tool motion. The path can save the empty travel time in the machining process and improve the overall machining efficiency. By using the control variable method and orthogonal test method, combined with an example, the influence of five important parameters that need to be optimized in the process of algorithm implementation on the quality of the optimal solution is analyzed and studied, and the rule of action is explored, which provides a reference for further improving the algorithm optimization results and improving the algorithm.

Key words: ant colony algorithm , path planning , hole group , TSP problem , orthogonal experiment

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