中国机械工程 ›› 2023, Vol. 34 ›› Issue (06): 703-711.DOI: 10.3969/j.issn.1004-132X.2023.06.009

• 智能制造 • 上一篇    下一篇

树结构主干分枝层级化的部件装配单元聚类划分

成彬1;张松松1;王晓明2   

  1. 1.西安建筑科技大学机电工程学院,西安,710055
    2.西安建筑科技大学理学院,西安,710055
  • 出版日期:2023-03-25 发布日期:2023-04-04
  • 通讯作者: 张松松(通信作者),男,1995年生,硕士研究生。研究方向为数字化设计与智能制造。E-mail:zhangsongsong96@163.com。
  • 作者简介:成彬,男,1972年生,教授、博士。研究方向为数字化智能化设计与制造、数字孪生技术等。E-mail:cheengbin@163.com。
  • 基金资助:
    国家自然科学基金 (51975449);陕西省自然科学基金(2021JM-360);陕西省教育厅科技计划(17JK0453)

Clustering of Component Assembly Units with Hierarchical Branching for Trunks of Tree Structures

CHENG Bin1;ZHANG Songsong1;WANG Xiaoming2   

  1. 1.School of Mechanical and Electrical Engineering,Xian University of Architecture and Technology,Xian,710055
    2.School of Science,Xian University of Architecture and Technology,Xian,710055
  • Online:2023-03-25 Published:2023-04-04

摘要: 针对部件装配过程中装配工作并行度低和特征偏差分析难的问题,提出了一种树结构主干分枝层级化的部件装配单元聚类划分方法。首先,根据零件间的装配关联构建部件树结构,分析分枝零件间的装配特征关联指标,建立指标系统及其应用规则表达分枝间的亲密度并建立亲密度矩阵,完成部件树主干表达;其次,以分枝间亲密度为初始输入,引入改进Dijkstra路径规划算法,利用算法本身的优势获得主干与多分枝间的局部最短路径最优解,构建主干-分枝层级矩阵,以实现部件树结构主干-分枝层级化,进而合并分枝完成装配单元聚类划分;最后,以单元划分结果进行虚拟装配,分析在物理车间执行总装时是否存在干涉情况以优化最终的划分结果。以某车用差速器装配体的装配单元聚类划分过程为实例验证了所提方法的可行性和有效性。

关键词: 装配单元, 亲密度, Dijkstra算法改进, 树结构层级化

Abstract: A method of clustering component assembly units with hierarchical branching for the trunks of tree structure was proposed aiming at the problems of low parallelism of assembly work and difficult analysis of feature deviation in the component assembly processes. Firstly, the component tree structure was constructed according to the assembly association among the parts, and the assembly feature association index among the branches was analyzed. The index system and the application rules were established to express the closeness between the branches, and the closeness matrix was constructed to complete the representation of the trunks of the component tree. Secondly, with the closeness between branches as the initial input, an improved Dijkstra path planning algorithm was introduced, and the optimal solution of the local shortest path between the trunk and multiple branches was obtained by using the advantages of the algorithm itself. The stem-branch hierarchy matrix was constructed to realize the stem-branch hierarchy of the component tree structure, and then the assembly unit clustering was completed by merging the branches. Finally, virtual assembly was carried out with the results of unit partition, and interference was analyzed in the physical workshops to optimize the final partition result. The feasibility and effectiveness of the proposed method were verified by an example of assembly unit clustering of a vehicle differential assembly. 

Key words: assembly unit, closeness, improved Dijkstra algorithm, hierarchical tree structure

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