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| Citation: |
LI R, ZHAO Y R, HUO S L, et al. Intelligent recognition algorithm for hull segment closure surface components based on improved PointNet++[J]. Chinese Journal of Ship Research, 2024, 19(6): 173–179 (in Chinese). DOI: 10.19693/j.issn.1673-3185.03744
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The point cloud data of hull segment closure obtained by a 3D scanner has such advantages 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 algorithm based on improved PointNet++ is proposed to realize the intelligent recognition of components for large-capacity hull segment convergence surface point cloud data.
Based on the hypervoxel growth theory, the hull segment closure point cloud data is segmented and simplified, and a hull segment closure point cloud data set is constructed and used to train a PointNet++ network improved by deep learning theory.
The convergence results of the network model on the training and testing sets of hull segment closure surface point cloud data tend to be stable, achieving an accuracy rate of 90.012% on the testing set.
The proposed method has good recognition ability and can achieve the intelligent recognition of hull segment closure surface components.
| [1] |
陈尚伟, 汪骥, 刘玉君, 等. 基于PointNet++的船体分段合拢面智能识别方法[J]. 船舶工程, 2019, 41(12): 138–141.
CHEN S W, WANG J, LIU Y J, et al. Intelligent recognition of block erection surface based on PointNet++[J]. Ship Engineering, 2019, 41(12): 138–141 (in Chinese).
|
| [2] |
李成坤. 船舶总段合拢面三维点云中对接特征的辨识方法研究[D]. 上海: 上海交通大学, 2021.
LI C K. Identification of hull surface docking features in laser-scanned point cloud[D]. Shanghai: Shanghai Jiao Tong University, 2021 (in Chinese).
|
| [3] |
陈攀, 尚保佑, 李天匀, 等. 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. doi: 10.19693/j.issn.1673-3185.03114
CHEN P, SHANG B Y, LI T Y, et al. Point cloud segmentation of flange laser scanning for ship shafting intelligent installation[J]. Chinese Journal of Ship Research, 2023, 18(6): 268–274 (in Chinese). doi: 10.19693/j.issn.1673-3185.03114
|
| [4] |
GAO Y F, PING C C, WANG L, et al. A simplification method for point cloud of T-profile steel plate for shipbuilding[J]. Algorithms, 2021, 14(7): 202. doi: 10.3390/a14070202
|
| [5] |
ZONG C J, WAN Z B. Container ship cell guide accuracy check technology based on improved 3D point cloud instance segmentation[J]. Brodogradnja, 2022, 73(1): 23–35. doi: 10.21278/brod73102
|
| [6] |
姜媛媛. 基于超体素区域增长的点云分割算法研究[D]. 西安: 西安电子科技大学, 2017.
JIANG Y Y. Research on supervoxel based region growing segmentation for point cloud data[D]. Xi’an: Xidian University, 2017 (in Chinese).
|
| [7] |
方程喜, 隋立春, 朱海雄. 用于公路勘测设计的LiDAR点云抽稀算法[J]. 测绘通报, 2017(10): 58–61,88.
FANG C X, SUI L C, ZHU H X. LiDAR point cloud thinning algorithm for road survey and design[J]. Bulletin of Surveying and Mapping, 2017(10): 58–61,88 (in Chinese).
|
| [8] |
陈薪宇. 基于PointNet++的道路场景点云分类方法研究[D]. 成都: 成都理工大学, 2021.
CHEN X Y. Research on point cloud classification of road scene based on PointNet++[D]. Chengdu: Chengdu University of Technology, 2021 (in Chinese).
|
| [9] |
QI C R, YI L, SU H, et al. PointNet++: deep hierarchical feature learning on point sets in a metric space[C]//Proceedings of the 31st International Conference on Neural Information Processing Systems. Long Beach: Curran Associates Inc. , 2017: 5105-5114.
|
| [10] |
李晓溪. 基于深度学习的三维点云语义分割技术研究[D]. 成都: 电子科技大学, 2021.
LI X X. Research on 3D point cloud semantic segmentation technology based on deep learning[D]. Chengdu: University of Electronic Science and Technology of China, 2021 (in Chinese).
|
| [11] |
TOMBARI F, SALTI S, DI STEFANO L. Unique signatures of histograms for local surface description[C]//The 11st European Conference on Computer Vision (ECCV 2010). Heraklion, Crete, Greece: Springer, 2010: 356−369.
|
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