A METHOD FOR EXTRACTING SUBSTATION EQUIPMENT BASED ON UAV LASER SCANNING POINT CLOUDS

Smart grid construction puts higher demands on the construction of 3D models of substations. However, duo to the complex and diverse structures of substation facilities, it is still a challenge to extract the fine three-dimensional structure of the substation facilities from the massive laser point...

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Main Authors: W. Yu, J. Xi, Z. Wu, W. Lei, C. Zhu, T. Tang
Format: Article
Language:English
Published: Copernicus Publications 2020-11-01
Series:The International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences
Online Access:https://www.int-arch-photogramm-remote-sens-spatial-inf-sci.net/XLIV-4-W3-2020/413/2020/isprs-archives-XLIV-4-W3-2020-413-2020.pdf
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author W. Yu
J. Xi
Z. Wu
W. Lei
C. Zhu
T. Tang
author_facet W. Yu
J. Xi
Z. Wu
W. Lei
C. Zhu
T. Tang
author_sort W. Yu
collection DOAJ
description Smart grid construction puts higher demands on the construction of 3D models of substations. However, duo to the complex and diverse structures of substation facilities, it is still a challenge to extract the fine three-dimensional structure of the substation facilities from the massive laser point clouds. To solve this problem, this paper proposes a method for extracting substation equipment from laser scanning point clouds. Firstly, in order to improve the processing efficiency and reduce the noises, the regular voxel grid sampling method is used to down-sample the input point cloud. Furthermore, the multi-scale morphological filtering algorithm is used to segment the point cloud into ground points and non-ground points. Based on the non-ground point cloud data, the substation region is extracted using plane detection in point clouds. Then, for the filtered substation point cloud data, a three-dimensional polygon prism segmentation algorithm based on point dimension feature is proposed to extract the substation equipment. Finally, the substation LiDAR point cloud data collected by the UAV laser scanning system is used to verify the algorithm, and the qualitative and quantitative comparison analysis between the detected results and the manually extracted results are carried out. The experimental results show that the proposed method can accurately extract the substation equipment structure from the laser point cloud data. The results are consistent with the manually extracted results, which demonstrate the great potential of the proposed method in substation extraction and power system 3D modelling applications.
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spelling doaj.art-0c2fe29d291c49eaafaa4285112b6afc2022-12-21T18:46:03ZengCopernicus PublicationsThe International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences1682-17502194-90342020-11-01XLIV-4-W3-202041341910.5194/isprs-archives-XLIV-4-W3-2020-413-2020A METHOD FOR EXTRACTING SUBSTATION EQUIPMENT BASED ON UAV LASER SCANNING POINT CLOUDSW. Yu0J. Xi1Z. Wu2W. Lei3C. Zhu4T. Tang5China Southern Power Grid Company Limited, 510700 Guangzhou, ChinaChina Southern Power Grid Digital Grid Research Institute Co. Ltd, Guangzhou, ChinaChina Southern Power Grid Company Limited, 510700 Guangzhou, ChinaChina Southern Power Grid Digital Grid Research Institute Co. Ltd, Guangzhou, ChinaChina Southern Power Grid Digital Grid Research Institute Co. Ltd, Guangzhou, ChinaWuhan Dynspai Technology Company Limited, Wuhan, ChinaSmart grid construction puts higher demands on the construction of 3D models of substations. However, duo to the complex and diverse structures of substation facilities, it is still a challenge to extract the fine three-dimensional structure of the substation facilities from the massive laser point clouds. To solve this problem, this paper proposes a method for extracting substation equipment from laser scanning point clouds. Firstly, in order to improve the processing efficiency and reduce the noises, the regular voxel grid sampling method is used to down-sample the input point cloud. Furthermore, the multi-scale morphological filtering algorithm is used to segment the point cloud into ground points and non-ground points. Based on the non-ground point cloud data, the substation region is extracted using plane detection in point clouds. Then, for the filtered substation point cloud data, a three-dimensional polygon prism segmentation algorithm based on point dimension feature is proposed to extract the substation equipment. Finally, the substation LiDAR point cloud data collected by the UAV laser scanning system is used to verify the algorithm, and the qualitative and quantitative comparison analysis between the detected results and the manually extracted results are carried out. The experimental results show that the proposed method can accurately extract the substation equipment structure from the laser point cloud data. The results are consistent with the manually extracted results, which demonstrate the great potential of the proposed method in substation extraction and power system 3D modelling applications.https://www.int-arch-photogramm-remote-sens-spatial-inf-sci.net/XLIV-4-W3-2020/413/2020/isprs-archives-XLIV-4-W3-2020-413-2020.pdf
spellingShingle W. Yu
J. Xi
Z. Wu
W. Lei
C. Zhu
T. Tang
A METHOD FOR EXTRACTING SUBSTATION EQUIPMENT BASED ON UAV LASER SCANNING POINT CLOUDS
The International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences
title A METHOD FOR EXTRACTING SUBSTATION EQUIPMENT BASED ON UAV LASER SCANNING POINT CLOUDS
title_full A METHOD FOR EXTRACTING SUBSTATION EQUIPMENT BASED ON UAV LASER SCANNING POINT CLOUDS
title_fullStr A METHOD FOR EXTRACTING SUBSTATION EQUIPMENT BASED ON UAV LASER SCANNING POINT CLOUDS
title_full_unstemmed A METHOD FOR EXTRACTING SUBSTATION EQUIPMENT BASED ON UAV LASER SCANNING POINT CLOUDS
title_short A METHOD FOR EXTRACTING SUBSTATION EQUIPMENT BASED ON UAV LASER SCANNING POINT CLOUDS
title_sort method for extracting substation equipment based on uav laser scanning point clouds
url https://www.int-arch-photogramm-remote-sens-spatial-inf-sci.net/XLIV-4-W3-2020/413/2020/isprs-archives-XLIV-4-W3-2020-413-2020.pdf
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