• 论文 •    

基于粒子群算法的产品拆卸序列规划方法

张秀芬,张树有   

  1. 1.浙江大学 CAD&CG国家重点实验室,浙江杭州310027;2.内蒙古工业大学 机械学院,内蒙古呼和浩特010051
  • 出版日期:2009-03-15 发布日期:2009-03-25

Product disassembly sequence planning based on particle swarm optimization algorithm

ZHANG Xiu-fen, ZHANG Shu-you   

  1. 1.State Key Lab of CAD&CG, Zhejiang University, Hangzhou 310027,China;2. College of Mechanical Engineer, Inner Mongolia University of Technology, Hohhot 010051,China
  • Online:2009-03-15 Published:2009-03-25

摘要: 为求取复杂产品的最优拆卸序列,建立了一种产品拆卸赋权混合图模型。利用该模型可以有效地表达组件间的拆卸优先关系,将零件的拆卸序列规划转化为图模型寻优的问题。基于该模型,推导出可拆卸性条件,并通过几何推理的方法产生可拆卸序列。针对复杂产品拆卸序列规划的特点,为了将赋权混合图模型映射到粒子群模型,给出了粒子速度和位置公式以及粒子进化规则,构建粒子适应度,应用粒子群算法实现了复杂产品的最优拆卸序列规划。最后,通过一个实例验证了该方法的有效性。

关键词: 拆卸, 拆卸序列规划, 粒子群优化算法, 拆卸赋权混合图, 机用虎钳

Abstract: To obtain the optimum disassembly sequence for complicated products, a novel Disassembly Weighted Hybrid Graph (DWHG) model was established to describe the mating contact and noncontact priority relationships among components. Then, disassembly sequence planning problem was mapped into the DWHG as an optimal path-searching problem. And the disassembly condition was deduced based on DWHG model, and feasible disassembly sequences were inferred through geometry inference method. Aiming at characteristics of complex products disassembly sequence planning, in order to map the DWHG model into particle swarm model, particles velocity, position formula and evolution rules were defined, particle fitness was also established. The optimal disassembly sequence planning was realized by particle swarm algorithm. Finally, a case study was given to illustrate effectiveness of the proposed method.

Key words: disassembly, disassembly sequence planning, particle swarm optimization algorithm, disassembly weighted hybrid graph, machine vice

中图分类号: