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邢宇飞, 李景春, 张景强. 考虑作业空间约束的并行拆卸序列规划算法[J]. 计算机辅助设计与图形学学报, 2018, 30(9): 1755-1764. DOI: 10.3724/SP.J.1089.2018.16858
引用本文: 邢宇飞, 李景春, 张景强. 考虑作业空间约束的并行拆卸序列规划算法[J]. 计算机辅助设计与图形学学报, 2018, 30(9): 1755-1764. DOI: 10.3724/SP.J.1089.2018.16858
Xing Yufei, Li Jingchun, Zhang Jingqiang. Parallel Disassembly Sequence Planning Method Considering Operation Space Constraints[J]. Journal of Computer-Aided Design & Computer Graphics, 2018, 30(9): 1755-1764. DOI: 10.3724/SP.J.1089.2018.16858
Citation: Xing Yufei, Li Jingchun, Zhang Jingqiang. Parallel Disassembly Sequence Planning Method Considering Operation Space Constraints[J]. Journal of Computer-Aided Design & Computer Graphics, 2018, 30(9): 1755-1764. DOI: 10.3724/SP.J.1089.2018.16858

考虑作业空间约束的并行拆卸序列规划算法

Parallel Disassembly Sequence Planning Method Considering Operation Space Constraints

  • 摘要: 为获取多人同时进行不同拆卸任务的并行拆卸序列,提出考虑拆卸作业空间约束的并行拆卸序列规划方法.首先从零件几何可行性、拆卸时间以及拆卸作业空间约束3个方面构建拆卸序列规划问题模型:为避免产生不可行序列,提出拆卸作业空间的快速提取和干涉检查方法;针对回收产品拆卸时间不确定的特点,引入区间数模型描述拆卸时间,从拆卸基本时间、拆卸工具准备时间和拆卸工位改变时间3个方面构建拆卸时间模型.然后基于协同工作原则设计蚁群搜索的等待机制,以求解并行的拆卸序列;为进一步提高算法求解复杂产品并行拆卸序列的质量和效率,采用具有自适应能力的信息素更新方式和蚂蚁选择策略对基本蚁群算法加以改进.通过一种锥齿轮减速器装配体实例对关键参数的取值进行讨论分析,并验证了该算法各项约束措施的有效性.

     

    Abstract: In order to obtain a parallel disassembly sequence in which multiple people perform different dis- assembly tasks at the same time, a parallel disassembly sequence planning method considering disassembly operation constraints is proposed. Firstly, the disassembly sequence planning problem model is constructed from three aspects: geometry feasibility, disassembly time and space constraint of disassembly work. In or- der to avoid infeasible sequences, a rapid extraction and interference checking method for the disassembly operation space is proposed; aiming at the uncertain characteristics of disassembly time of recycled products, the interval number model is introduced to describe the disassembly time, the disassembly model contains three factors is constructed, which include the basic disassembly time, the disassembly tool preparation time and the disassembly station change time. Then the waiting mechanism of the ant colony search is designed based on the principle of collaborative work to acquire the parallel disassembly sequence solution. In order to further improve the quality and efficiency of the algorithm for solving the parallel disassembly sequence of complex products, the pheromone update method with self-adaptive capabilities and ant selection strategy are utilized to improve the basic ant colony algorithm. Finally, a bevel gear reducer is utilized as an example to discuss and analysis the value of key parameters, and the effectiveness of the constraint measures of the algorithm are verified.

     

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