王嘉瑞, 崔海华, 史建猛, 高凯元, 国荣辉. 基于特征定位的航空航天制孔多视测量拼接方法[J]. 应用光学, 2023, 44(4): 834-841. DOI: 10.5768/JAO202344.0403004
引用本文: 王嘉瑞, 崔海华, 史建猛, 高凯元, 国荣辉. 基于特征定位的航空航天制孔多视测量拼接方法[J]. 应用光学, 2023, 44(4): 834-841. DOI: 10.5768/JAO202344.0403004
WANG Jiarui, CUI Haihua, SHI Jianmeng, GAO Kaiyuan, GUO Ronghui. Multi-view measurement registration method of aerospace hole making based on feature location[J]. Journal of Applied Optics, 2023, 44(4): 834-841. DOI: 10.5768/JAO202344.0403004
Citation: WANG Jiarui, CUI Haihua, SHI Jianmeng, GAO Kaiyuan, GUO Ronghui. Multi-view measurement registration method of aerospace hole making based on feature location[J]. Journal of Applied Optics, 2023, 44(4): 834-841. DOI: 10.5768/JAO202344.0403004

基于特征定位的航空航天制孔多视测量拼接方法

Multi-view measurement registration method of aerospace hole making based on feature location

  • 摘要: 为满足航空航天大部件对制孔质量的数字化原位检测需求,提出一种基于特征板的制孔多视点云拼接方法,实现孔壁完整三维形貌重建与检测。分析制孔多视检测的需求,提出采用特征定位板辅助的多视点云配准方法。介绍了内角不等四边形特征板的设计与相应的点云分割、识别算法。说明基于特征自定位的多视点云拼接及参数提取方法。结合机械臂搭建实验平台,对常用钛、铝及复合材料的试件模拟原位检测,结果显示各平均误差分别为0.011 mm、0.034 mm、0.041 mm,验证了配准算法的可靠性;并对比传统单视与该方法检测结果,体现该方法的鲁棒性。

     

    Abstract: In order to meet the needs of digital in-situ detection of hole making quality for aerospace large components, a multi-view point cloud registration method based on feature locating plate was proposed, which realized the reconstruction and detection of 3D morphology of integral hole wall. Firstly, the requirements of multi-view detection of hole making were analyzed, and a method of multi-view point cloud registration assisted by feature locating plate was proposed. Then, the design of quadrilateral feature plate with unequal interior angles and the corresponding point cloud segmentation as well as recognition algorithm were introduced. Also, the method of multi-view point cloud registration and parameter extraction based on feature self-localization was described. Finally, combined the mechanical arm to build the experimental platform, the titanium, aluminum and composite materials commonly used in aerospace were tested, and the average error was 0.011 mm, 0.034 mm and 0.041 mm, respectively, which verified the reliability of the system. The robustness of this method was demonstrated by comparing the detection results of traditional single-view method with that of the proposed method.

     

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