• CN:11-2187/TH
  • ISSN:0577-6686

›› 2010, Vol. 46 ›› Issue (11): 172-178.

• 论文 • 上一篇    下一篇

面向复杂机械产品的目标选择性拆卸序列规划方法

张秀芬;张树有;伊国栋;楼锡银   

  1. 浙江大学机械工程学系;内蒙古工业大学机械学院
  • 发布日期:2010-06-05

Object Selective Disassembly Sequence Planning for Complex Mechanical Products

ZHANG Xiufen;ZHANG Shuyou;YI Guodong;LOU Xiyin   

  1. Department of Mechanical Engineering, Zhejiang University College of Mechanical Engineering, Inner Mongolia University of Technology
  • Published:2010-06-05

摘要: 为提高复杂产品目标选择性拆卸序列规划的效率,基于自底向上的思想,提出一种拆卸混合图和粒子群算法相结合的方法。为了表达产品零部件间的内部约束和拆卸优先关系,建立产品拆卸混合图模型,并推导出可拆卸性约束表达式。基于粒子群优化算法,给出目标选择性拆卸序列规划问题的数学描述和粒子适应度计算公式。利用图深度搜索算法确定拆卸目标位置,并设计目标驱动递归推理法生成可行目标选择性拆卸序列,以此初始化粒子,通过粒子进化,实现了复杂产品目标选择性拆卸序列最优化的快速求解。以一个全自动洗衣机为拆卸实例,用所提方法进行目标选择性拆卸序列规划求解,通过分析试验结果,证明了该方法的有效性和可行性。

关键词: 拆卸混合图, 拆卸序列规划, 选择性拆卸

Abstract: In order to improve the efficiency of object selective disassembly sequence planning(OSDSP) for complex mechanical products, an approach based on bottom-up ideas is proposed, which combines the disassembly hybrid graph model(DHGM) with particle swarm optimization (PSO) algorithm. The DHGM is constructed to describe the constraint and disassembly priority relationships among constituting components of product. Furthermore, the disassemblability constraint expression is deduced from it. Based on PSO, both the mathematic description of OSDSP and the particle fitness (i.e., objective function) are given. Depth first search(DFS) is carried out to locate the selective component, then a new object-driven recursive reasoning method is designed to generate possible disassembly sequences which are used to initialize the particles. PSO is used to obtain the optimum disassembly sequence effectively. A full-automatic washer case study proves the validity and feasibility of the proposed method .

Key words: Disassembly hybrid graph, Disassembly sequence planning, Selective disassembly

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