Digital reconstruction of substation equipment and facility layout via LiDAR point cloud registration

被引:0
作者
Wang, Fei [1 ,2 ]
Fan, Zikai [1 ,2 ]
Miao, Yun [1 ,2 ]
Ren, Jiayi [1 ,2 ]
Luo, Yuchao [1 ,2 ]
机构
[1] State Grid Jiangsu Elect Power Co Ltd, Econ Res Inst, Nanjing, Jiangsu, Peoples R China
[2] State Grid Jiangsu Elect Power Design Consulting, Nanjing, Jiangsu, Peoples R China
关键词
Reconstruction; substation; point cloud registration; point cloud segmentation; POWER-LINES; EXTRACTION;
D O I
10.3233/JCM-247162
中图分类号
T [工业技术];
学科分类号
08 ;
摘要
Generating as-built Building information models (BIMs) is promising in power substation construction projects because they can reflect the actual conditions of facilities. However, traditional manual-designed BIMs are different from real-world scenarios due to reality gaps. In this paper, we present a new method of reconstructing the layout of power equipment and facilities in substations using LIDAR point clouds. The proposed method extracts electric equipment and facilities via object segmentation and model retrieval. In particular, we investigate PFH, FPFH and SHOT descriptors for the 3D-SIFT keypoints in the 3D shape retrieval of complex electric equipment and facilities. After the best-match model is retrieved from a model library, the layout of typical electric equipment and facilities is reconstructed by aligning the model to the scene point cloud via point cloud registration. Experimental results validate the effectiveness of the proposed method. The proposed method enhances the efficiency of generating 3D models of power substations.
引用
收藏
页码:1269 / 1281
页数:13
相关论文
共 22 条
  • [1] Bridson Robert, 2007, ACM SIGGRAPH 2007 Sketches. SIGGRAPH'07, V10, P1, DOI [DOI 10.1145/1278780.1278807, 10.1145/1278780.1278807]
  • [2] A two-phase approach for expression invariant 3D face recognition using fine-tuned VGG-16 and 3D-SIFT descriptors
    Devi, Suganya P. R.
    Baskaran, R.
    [J]. MULTIMEDIA TOOLS AND APPLICATIONS, 2023, 82 (15) : 23873 - 23890
  • [3] AlignBodyNet: Deep Learning-Based Alignment of Non-Overlapping Partial Body Point Clouds From a Single Depth Camera
    Hu, Pengpeng
    Ho, Edmond S. L.
    Munteanu, Adrian
    [J]. IEEE TRANSACTIONS ON INSTRUMENTATION AND MEASUREMENT, 2023, 72
  • [4] Huang Z, 2019, Lecture Notes in Computer Science, V11857
  • [5] Reconstruction of 3D shapes with B-spline surface using diagonal approximation BFGS methods
    Jahanshahloo, Almas
    Ebrahimi, Alireza
    [J]. MULTIMEDIA TOOLS AND APPLICATIONS, 2022, 81 (26) : 38091 - 38111
  • [6] Measurement and monitoring of overhead transmission line sag in smart grid: A review
    Mahin, Ayman Uddin
    Islam, Shama Naz
    Ahmed, Fabliha
    Hossain, Md Farhad
    [J]. IET GENERATION TRANSMISSION & DISTRIBUTION, 2022, 16 (01) : 1 - 18
  • [7] A 3D Surface Reconstruction Method Based on Delaunay Triangulation
    Miao, Wenjuan
    Liu, Yiguang
    Shi, Xuelei
    Feng, Jingming
    Xue, Kai
    [J]. IMAGE AND GRAPHICS, ICIG 2019, PT II, 2019, 11902 : 40 - 51
  • [8] Myronenko A., 2007, ADV NEURAL INFORM PR, V19, P1009, DOI DOI 10.1109/TPAMI.20
  • [9] Peng Chi, 2019, 2019 3rd International Conference on Electronic Information Technology and Computer Engineering (EITCE). Proceedings, P1395, DOI 10.1109/EITCE47263.2019.9094966
  • [10] SHOT: Unique signatures of histograms for surface and texture description
    Salti, Samuele
    Tombari, Federico
    Di Stefano, Luigi
    [J]. COMPUTER VISION AND IMAGE UNDERSTANDING, 2014, 125 : 251 - 264