中国舰船研究2023，Vol.18Issue(6)：268-274,7.DOI:10.19693/j.issn.1673-3185.03114
面向船舶轴系智能安装的法兰激光扫描点云分割研究
Point cloud segmentation of flange laser scanning for ship shafting intelligent installation
摘要
Abstract
[Objectives]Laser scanning technology used in the intelligent installation of ship shafting has such advantages as non-contact,high-speed scanning and high-precision imaging.The laser point cloud data includes the size,position and direction information of space objects.Point cloud segmentation can greatly re-duce the calculation scale of the data and improve the measurement efficiency of the relative pose of the butt flange.[Methods]In this paper,deep learning theory is used to study point cloud segmentation and obtain a point cloud dataset of flange parts.The PointNet model is used for training.Optimization strategies are formu-lated in three aspects,namely dropout regularization,learning rate attenuation and point cloud data enhance-ment,then tested on a ship shafting intelligent installation platform.[Results]The convergence results of the model tend to be stable,with the accuracy of the training set reaching 0.88 and that of the verification set reaching 0.65.The flange point cloud segmentation experiment shows clear contour edges.[Conclusion]The results of this study show that the proposed method has good convergence and generalization perform-ance,and can improve the efficiency of ship shafting intelligent installation.关键词
船舶轴系/智能安装/深度学习/点云分割Key words
ship shafting/intelligent installation/deep learning/point cloud segmentation分类
交通运输引用本文复制引用
陈攀,尚保佑,李天匀,李维嘉,朱翔..面向船舶轴系智能安装的法兰激光扫描点云分割研究[J].中国舰船研究,2023,18(6):268-274,7.基金项目
国家自然科学基金资助项目(51839005) （51839005）
