上海交通大学学报(自然版) ›› 2013, Vol. 47 ›› Issue (05): 840-845.

• 交通运输 • 上一篇    下一篇

基于高斯映射的多误差源复杂结构匹配分析与优化

许川,吴昊,王华,高翔   

  1. (上海交通大学 上海市复杂薄板结构数字化制造重点实验室, 上海 200240)
     
  • 收稿日期:2012-05-14 出版日期:2013-05-28 发布日期:2013-05-28
  • 基金资助:

    国家自然科学基金项目(50905117),教育部高等学校学科创新引智计划(B06012),上海交通大学SMC晨星青年学者奖励计划(2010)资助

Matching Optimization Analysis of Complex Structure with Multiple Error Sources Based on Gaussian Mapping

XU Chuan,WU Hao,WANG Hua,GAO Xiang
  

  1. (Shanghai Key Laboratory of Digital Manufacture for ThinWalled Structures, Shanghai Jiaotong University, Shanghai 200240, China)
  • Received:2012-05-14 Online:2013-05-28 Published:2013-05-28

摘要:

为了提高汽车尾灯区域的匹配质量,以高斯映射和数理统计为基础,并借鉴Hausdorff距离的概念,在高斯尺度空间量化匹配状态,建立匹配优化的目标函数和辅助检验目标参数,通过编程计算而寻找最佳匹配调整方式.同时,在对所建优化方法的有效性进行验证和分析的基础上,将其用于工程实际中.结果表明,所提出的优化方法的可操作性较强,能够有效提高轿车尾灯区域的匹配质量.

 
 

关键词: 高斯映射, 尾灯区域, 匹配, 质量控制, Hausdorff距离

Abstract:

In order to improve the assembly quality of the automobile tail light area, on the basis of Gaussian image and mathematical statistics, taking the Hausdorff distance for reference, this paper quantified the matching status on Gaussian scale space, and established the objective function and the subsidiary verification target parameter for optimization, to find the best matching adjustment method by computer program. Based on the verification and analysis of the validity of the theory above, the test on the application of actual engineering data shows that it is effectual for improving the assembly quality with strong operational.
 

Key words: Gaussian mapping, tail light area, assembly, quality control, Hausdorff distance

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