中国机械工程 ›› 2025, Vol. 36 ›› Issue (07): 1636-1649.DOI: 10.3969/j.issn.1004-132X.2025.07.026

• 工程前沿 • 上一篇    下一篇

船舶大构件几何特征建模及装配干涉检测方法

顾世民1;刘金锋1*;钱天龙2;景旭文1;王学敏2;毛包晨1;沈阳2;陈宇1   

  1. 1.江苏科技大学机械工程学院,镇江,212000
    2.扬州中远海运重工有限公司,扬州,225200

  • 出版日期:2025-07-25 发布日期:2025-09-04
  • 作者简介:顾世民,男,2000年生,硕士研究生。研究方向为船舶智能制造使能技术。E-mail:1464485340@qq.com。
  • 基金资助:
    国家自然科学基金(52371324,52075229);船舶总装建造数字化船厂研究与示范项目(CBG01N23-05-01)

Geometric Feature Modeling and Assembly Interference Detection Method for Large Ship Components

GU Shimin1;LIU Jinfeng1,*;QIAN Tianlong2;JING Xuwen1;WANG Xuemin2;MAO Baochen1;SHEN Yang2;CHEN Yu1   

  1. 1.Jiangsu University of Science and Technology,Zhenjiang,Jiangsu,212000
    2.COSCO Shipping Heavy Industry(Yangzhou) Co.,Ltd.,Yangzhou,Jiangsu,225200

  • Online:2025-07-25 Published:2025-09-04

摘要: 船舶构件制造和装配中的制造误差与装焊变形影响肋板拉入装配的成功率和效率。提出了基于几何特征的船舶大尺寸构件快速建模及装配干涉检测方法。该方法先定义装配特征,再利用改进的ASPacNet准确识别装配特征,接着进行局部重建与拼接,最后通过时间域间断配合间隙计算方法检测装配干涉。实验显示,该方法在船舶大尺寸构件上的建模效率较传统方法提高66.01%,建模均方根误差为0.206 mm,干涉检测准确率达98.81%,能有效减少试装,为船舶大构件高效装配提供新技术手段。

关键词: 装配特征识别, 快速建模, 船舶大尺度构件, 肋板拉入装配, 精度检测

Abstract: Manufacturing errors and welding deformations in manufacturing and assembly of ship components affected the success rate and efficiency of rib plate pulling-in assembly. Therefore, a rapid modeling and assembly interference detection method for large ship components was proposed based on geometric features. The method defined assembly features, used the improved ASPacNet to accurately identify the assembly features, carried local reconstruction and splicing out, and detected assembly interference through a time-domain intermittent fit clearance calculation method. Experiments show that the modeling efficiency of the method for large ship components is 66.01% higher than that of traditional methods, the root mean square error of modeling is as 0.206 mm, and the interference detection accuracy reaches 98.81%. It may effectively reduce trial assembly and provide a new technical means for the efficient assembly of large ship components.

Key words:  , assembly feature recognition, rapid modeling, large-scale components of ship, rib pull-in assembly, precision detection

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