摘要
针对目前铆钉孔特征提取方法的限制多、自动化程度低等问题,提出了一种基于散乱点云的铆钉孔自动识别与特征参数提取算法。通过每个点的k邻域点分布情况提取点云边界点,利用欧式距离聚类对其进行分割得到属于不同边界特征的点云块,随后依据椭圆拟合结果提取铆钉孔边界。借助k近邻搜索算法寻找铆钉孔边界邻域点云,进而构造铆钉孔的实际定位面,并将边界点投影至定位面以拟合端面圆。试验验证表明,本文提出的方法能够精确识别并提取铆钉孔,孔位提取精度可达0.029mm。
Aiming at the limitations and the low automations of the current rivet hole feature extraction method,an automatic identification and features parameter extraction method for rivet hole based on scattered point cloud is proposed.The point cloud boundary points are extracted by the k neighbor point distribution of each point,and the point cloud blocks belonging to different boundary features are obtained by using Euclidean distance clustering,and then according to the ellipse fitting result,the rivet hole boundaries are extracted.The k nearest neighbor search algorithm is used to find the point cloud of the rivet hole boundary neighborhood,and then the actual positioning plane of the rivet hole is constructed,and the boundary point is projected to the positioning plane to fit the end circle.The experiments show that the method can accurately identify and extract the rivet holes and that the center position extraction accuracy can reach 0.029 mm.
作者
田清廉
熊天辰
黄翔
李泷杲
郝龙
TIAN Qinglian;XIONG Tianchen;HUANG Xiang;LI Shuanggao;HAO Long(College of Mechanical and Electrical Engineering,Nanjing University of Aeronautics and Astronautics,Nanjing 210016,China;Jiangxi Aerospace Haihong Test&Control Co.,Ltd.,Nanchang 330024,China)
出处
《航空制造技术》
CSCD
北大核心
2022年第7期83-89,共7页
Aeronautical Manufacturing Technology
基金
国防基础科研计划资助(JCKY2020605C014)。
关键词
铆钉孔
散乱点云
特征识别
特征提取
圆孔检测
Rivet hole
Scattered point cloud
Feature recognition
Feature extraction
Circular hole detection
