中国舰船研究2024，Vol.19Issue(6)：173-179,7.DOI:10.19693/j.issn.1673-3185.03744
基于改进PointNet++的船体分段合拢面构件智能识别算法研究
Intelligent recognition algorithm for hull segment closure surface components based on improved PointNet++
摘要
Abstract
[Objectives]The point cloud data of hull segment closure obtained by a 3D scanner has such ad-vantages as high precision and large data volume,and can accurately reflect the construction status of segment closure.Since the existing PointNet++network is unable to process large-capacity point cloud data,an al-gorithm based on improved PointNet++is proposed to realize the intelligent recognition of components for large-capacity hull segment convergence surface point cloud data.[Methods]Based on the hypervoxel growth theory,the hull segment closure point cloud data is segmented and simplified,and a hull segment clos-ure point cloud data set is constructed and used to train a PointNet++network improved by deep learning the-ory.[Results]The convergence results of the network model on the training and testing sets of hull seg-ment closure surface point cloud data tend to be stable,achieving an accuracy rate of 90.012%on the testing set.[Conclusions]The proposed method has good recognition ability and can achieve the intelligent recog-nition of hull segment closure surface components.关键词
船舶建造/人工智能/船体分段合拢面/点云数据/超体素生长/PointNet++/智能识别Key words
shipbuilding/artificial intelligence/hull segment closure surface/point cloud data/hyper-voxel growth/PointNet++/intelligent identification分类
交通工程引用本文复制引用
李瑞,赵怡荣,霍世霖,汪骥,史卫东..基于改进PointNet++的船体分段合拢面构件智能识别算法研究[J].中国舰船研究,2024,19(6):173-179,7.基金项目
国家自然科学基金资助项目(51979033) （51979033）
大连市科技创新基金资助项目(2021JJ12GX032) （2021JJ12GX032）
