中国机械工程 ›› 2025, Vol. 36 ›› Issue (06): 1269-1279.DOI: 10.3969/j.issn.1004-132X.2025.06.014

• 可持续制造 • 上一篇    下一篇

基于拆卸信息提取的多零件堆叠结构设备动态干涉分析方法

王云帆1,2;朱利斌1,2;崔创创1,2;黄海鸿1,2*   

  1. 1.合肥工业大学机械工程学院,合肥,230009
    2.机电产品低碳循环利用技术与装备安徽省重点实验室,合肥,230009

  • 出版日期:2025-06-25 发布日期:2025-08-04
  • 作者简介:王云帆,女,2000年生,硕士研究生。研究方向为可拆卸性设计。E-mail:15234511210@163.com。

DIA Method for Multi-part Stacked Structure Devices Based on Disassembly Information Extraction

WANG Yunfan1,2;ZHU Libin1,2;CUI Chuangchuang1,2;HUANG Haihong1,2*   

  1. 1.School of Mechanical Engineering,Hefei University of Technology,Hefei,230009
    2.Anhui Province Key Laboratory of Low Carbon Recycling Technology and Equipment for
    Mechanical and Electrical Products,Hefei,230009

  • Online:2025-06-25 Published:2025-08-04

摘要: 针对设备多零件堆叠结构导致零件拆卸干涉检测效率与精度低的问题,提出一种基于拆卸信息提取的多零件堆叠结构设备动态干涉分析(DIA)方法,以提高拆卸信息获取的准确性、缩短零件拆卸时间。通过包容盒与实体相交两阶段干涉检测,提取设计模型中的拆卸信息并将其量化为优先矩阵;结合装配体与零件的双坐标系变换,精确提取动态变化的拆卸信息。为验证该方法的可行性与有效性,通过CAD设计模型实验,分别获得DIA与传统干涉检测方法生成的优先矩阵,并以此作为结构拆卸约束信息,输入蝴蝶遗传新型混合优化算法寻优以获得最优拆卸序列。实验结果表明,DIA生成优先矩阵的准确性比传统方法提高了28.57%,所获最优拆卸序列的拆卸时间缩短了3.31%。

关键词: 可拆卸设计, 拆卸信息提取, 动态干涉分析, 蝴蝶遗传优化算法

Abstract: Aiming at the problems of low efficiency and accuracy of disassembly interference detection due to the multi-part stacked structure devices, a DIA method was proposed based on DIE to improve the accuracy of disassembly information acquisition and shorten the disassembly time of parts. The disassembly information in the design model was extracted and quantified as a priority matrix through two-stage interference detection involving the boundary box and solid intersection. The dynamically changing disassembly information was accurately extracted by combining the dual coordinate system transformation of the assembly and parts. In order to verify the feasibility and effectiveness of this method, CAD design model experiments were conducted. The priority matrix generated by DIA and traditional interference detection methods were obtained and used as structural constraint information, which were input into the BOA-GA to search for the optimal disassembly sequence. The experimental results demonstrate that the accuracy of the priority matrix generated by DIA is increased by 28.57% compared with the traditional method, and the disassembly time of the optimal sequence is shortened by 3.31%.

Key words: design for disassembly, disassembly information extraction(DIE), dynamic interference analysis(DIA), butterfly-genetic hybrid optimization algorithm(BOA-GA)

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