Reverse modelling method of transmission tower based on intelligent identification of key points of point cloud projection

被引:0
|
作者
He F. [1 ]
Hu Y. [1 ]
Liu Y. [1 ]
Li G. [1 ]
机构
[1] Hubei Key Laboratory of Intelligent Vision Based Monitoring for Hydroelectric Engineering, Hubei Province Engineering Technology Research Center for Construction Quality Testing Equipments, China Three Gorges University, Yichang, Hubei
[2] State Grid Shiyan Electric Power Supply Company Transmission Maintenance Branch, State Grid, Shiyan, Hubei
关键词
electric transmission tower; key point identification; LSTM; point cloud data; reverse modelling;
D O I
10.1504/ijwmc.2023.131334
中图分类号
学科分类号
摘要
At present, neither image-based oblique photographic modelling nor laser point cloud modelling can generate high-precision solid models of transmission towers. In this paper, a fast reverse modelling method based on deep learning for the identification of key points of the transmission tower point cloud plane projection and high accuracy is proposed. This method first transforms the 3D point cloud data into two-dimensional image data through orthographic projection, then uses CNN and LSTM two deep learning networks to predict the number of variable key points in the image and finally calculates the corresponding coordinates in 3D space through the key points in the twodimensional image. Through this method, the size and position of transmission tower components are obtained, which can realise fast and high-precision reverse modelling of transmission tower. © 2023 Inderscience Enterprises Ltd.
引用
收藏
页码:390 / 399
页数:9
相关论文
共 50 条
  • [1] Intelligent identification algorithm and key point detection of abnormal vibration of transmission tower based on machine learning
    Hong, Huawei
    Wu, Kaibin
    Yue, Mengmeng
    Dai, An
    INTERNATIONAL JOURNAL OF EMERGING ELECTRIC POWER SYSTEMS, 2023, 24 (04) : 423 - 432
  • [2] Intelligent Point Cloud Edge Detection Method Based on Projection Transformation
    Zhu, Juan
    Yue, Xiaofeng
    Huang, Jipeng
    Huang, Zongwei
    WIRELESS COMMUNICATIONS & MOBILE COMPUTING, 2021, 2021
  • [3] Finite Element Modelling of a Transmission Steel Lattice Tower Based on LiDAR Point Cloud Data
    Wrzosek, Filip
    ce/papers, 2023, 6 (3-4) : 1174 - 1178
  • [4] A laser point cloud registration method for local geometric key points
    Wang, Zhe
    Gao, Pengwei
    Jin, Yaxiong
    Zhai, Boqiang
    INTERNATIONAL CONFERENCE ON COMPUTER VISION, APPLICATION, AND DESIGN (CVAD 2021), 2021, 12155
  • [5] Drawing curves onto a cloud of points for point-based modelling
    Azariadis, PN
    Sapidis, NS
    COMPUTER-AIDED DESIGN, 2005, 37 (01) : 109 - 122
  • [6] Point Cloud Registration Method Based on Key Point Extraction with Small Overlap
    Lu J.
    Shao H.-X.
    Wang W.
    Fan Z.-J.
    Xia G.-H.
    Beijing Ligong Daxue Xuebao/Transaction of Beijing Institute of Technology, 2020, 40 (04): : 409 - 415
  • [7] Flexibility Method of Damage Identification for Transmission Tower Based on Signal Amplitude Vector
    Zhou, Ling
    Cheng, Hua
    Wang, Zhonggang
    Zhou, Junlong
    FRONTIERS OF GREEN BUILDING, MATERIALS AND CIVIL ENGINEERING, PTS 1-8, 2011, 71-78 : 3942 - 3945
  • [8] ROI Method for Displacement Identification of Power Transmission Tower Based on Computer Vision
    Zhang, Kai
    Sun, Chao
    Liu, Jiahao
    Li, Yuxue
    Tian, Li
    Zhendong Ceshi Yu Zhenduan/Journal of Vibration, Measurement and Diagnosis, 2024, 44 (05): : 849 - 856
  • [9] Intelligent identification of rock mass structural based on point cloud deep learning technology
    Li, Xu
    Song, Zhanping
    Zhi, Bin
    Pu, Jiangyong
    Meng, Chen
    CONSTRUCTION AND BUILDING MATERIALS, 2024, 456
  • [10] Texture Mapping Method of Laser Point Cloud and Digital Image Based on Projection Transformation
    Cai, Yun
    Li, Hao
    Wu, Mingfei
    Yang, Biao
    ENVIRONMENTAL ENGINEERING, PTS 1-4, 2014, 864-867 : 2792 - 2798