[1]杨润党, 续爱民, 甄希金, 等. 船舶薄板平面分段产线技术发展及应用现状[J]. 船舶工程, 2022, 44(10):16-23.
YANG Rundang, XU Aimin, ZHEN Xijin, et al. Development and Application Status of Ship Thin Plate Plane Sectional Production Line Technology[J]. Ship Engineering, 2022, 44(10):16-23.
[2]王传何, 蔡秋艳, 刘杰强, 等. 面向肋板拉入装配的设备集成监测与智能维护系统研究[J]. 船舶工程, 2023, 45(4):144-151.
WANG Chuanhe, CAI Qiuyan, LIU Jieqiang, et al. Study on Equipment Integrated Monitoring and Intelligent Maintenance System for Floor Pull-in Assembly[J]. Ship Engineering, 2023, 45(4):144-151.
[3]王进锋, 喻正昌, 李丽. 肋板拉入法工艺研究[J]. 船舶标准化工程师, 2015, 48(5):27-29.
WANG Jinfeng, YU Zhengchang, LI Li. Technical Research of Floor Pulled-in Method[J]. Ship Standardization Engineer, 2015, 48(5):27-29.
[4]刘检华, 孙清超, 程晖, 等. 产品装配技术的研究现状、技术内涵及发展趋势[J]. 机械工程学报, 2018, 54(11):2-28.
LIU Jianhua, SUN Qingchao, CHENG Hui, et al. The State-of-the-art, Connotation and Developing Trends of the Products Assembly Technology[J]. Journal of Mechanical Engineering, 2018, 54(11):2-28.
[5]肖龙辉, 裴志勇, 徐文君, 等. 船体结构数字孪生技术及应用[J]. 船舶力学, 2023, 27(4):573-582.
XIAO Longhui, PEI Zhiyong, XU Wenjun, et al. Digital Twin Technology and Its Application in Ship Structural Field[J]. Journal of Ship Mechanics, 2023, 27(4):573-582.
[6]韩玉超,彭飞,王中,等. 点云在船舶建造领域的应用进展与展望[C]∥中国造船工程学会.2022年数字化造船学术交流会议论文集.上海,2022:265-270.
[7]杨泽鑫, 程效军, 李泉, 等. 平面舱壁类型的船舱点云分割方法[J]. 中国激光, 2017, 44(10):1010006.
YANG Zexin, CHENG Xiaojun, LI Quan, et al. Segmentation of Point Cloud in Tank of Plane Bulkhead Type[J]. Chinese Journal of Lasers, 2017, 44(10):1010006.
[8]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 Shangwei, WANG Ji, LIU Yujun, et al. Intelligent Recognition of Block Erection Surface Based on PointNet++[J]. Ship Engineering, 2019, 41(12):138-141.
[9]吕超凡, 黄德林, 刘天元, 等. 基于点云深度学习的加工特征识别方法[J]. 计算机集成制造系统, 2023, 29(3):752-762.
LYU Chaofan, HUANG Delin, LIU Tianyuan, et al. Manufacturing Feature Recognition Based on Point Cloud Deep Learning[J]. Computer Integrated Manufacturing Systems, 2023, 29(3):752-762.
[10]倪崇本, 李志月, 杨荣淇. 基于法向一致性的船体板架结构点云识别[J]. 船舶工程, 2022, 44(2):123-127.
NI Chongben, LI Zhiyue, YANG Rongqi. Recognition of Hull Point Cloud Basing on the Normal Consensus[J]. Ship Engineering, 2022, 44(2):123-127.
[11]刘建成, 程良伦, 刘斯亮. 一种优化的船体外板三维点云数据提取方法[J]. 船舶工程, 2015, 37(8):74-78.
LIU Jiancheng, CHENG Lianglun, LIU Siliang. Optimization of Hull Outer Steel Plate Three-dimensional Extraction Method for Point Cloud Data[J]. Ship Engineering, 2015, 37(8):74-78.
[12]朱帅臣, 习俊通. 大型船舶平直板零件尺寸柔性测量方法[J]. 应用激光, 2021, 41(5):1070-1076.
ZHU Shuaichen, XI Juntong. Flexible Measurement Method for Size of Straight Plate Parts of Large Ships[J]. Applied Laser, 2021, 41(5):1070-1076.
[13]MIAO Yang, LI Changan, LI Zhan, et al. A Novel Algorithm of Ship Structure Modeling and Target Identification Based on Point Cloud for Automation in Bulk Cargo Terminals[J]. Measurement and Control, 2021, 54(3/4):155-163.
[14]LI Yuan, LI Zhan, YANG Yipeng, et al. A Fast Recognition Algorithm of Ship Hatch in Bulk Cargo Terminal Based on Point Cloud Contour Extraction[J]. Measurement and Control, 2023, 56(1/2):228-236.
[15]许少秋, 余扬帆, 郭俊林, 等. 基于大场景三维点云的集装箱船关键绑扎特征识别与重建[J]. 船舶工程, 2022, 44(6):127-133.
XU Shaoqiu, YU Yangfan, GUO Junlin, et al. Identification and Reconstruction of Key Lashing Features of Container Ships Based on Large Scene 3D Point Cloud[J]. Ship Engineering, 2022, 44(6):127-133.
[16]郭志飞, 张勇, 张敬芳, 等. 曲板加工点云数据重构和自动调型技术[J]. 船舶工程, 2022, 44(10):22-26.
GUO Zhifei, ZHANG Yong, ZHANG Jingfang, et al. Reconstruction and Automatic Shaping Technology of Bending Plate Processing Point Cloud Data[J]. Ship Engineering, 2022, 44(10):22-26.
[17]DUAN Wenyang, ZHANG Peixin, HUANG Limin, et al. Ship Hull Surface Reconstruction from Scattered Points Cloud Using an RBF Neural Network Mapping Technology[J]. Computers & Structures, 2023, 281:107012.[LinkOut]
[18]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, 2017:5105-5114.
[19]YAN Xu, ZHENG Chaoda, LI Zhen, et al. PointASNL:Robust Point Clouds Processing Using Nonlocal Neural Networks with Adaptive Sampling[C]∥2020 IEEE/CVF Conference on Computer Vision and Pattern Recognition(CVPR). Seattle, 2020:5588-5597.
|