3D point cloud recognition of substation equipment based on plane detection
Substation equipment identification is a key step in the process of intelligent substation designing. The target recognition of 3D point cloud of substation equipment firstly uses a 3D laser scanner to obtain the 3D point cloud data that can express the surface shape and spatial position of a substa...
| Main Authors: | , , |
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| Format: | Article |
| Language: | English |
| Published: |
Elsevier
2022-09-01
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| Series: | Results in Engineering |
| Subjects: | |
| Online Access: | http://www.sciencedirect.com/science/article/pii/S2590123022002158 |
| _version_ | 1828177320081358848 |
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| author | Qianjin Yuan Yong Luo HeShan Wang |
| author_facet | Qianjin Yuan Yong Luo HeShan Wang |
| author_sort | Qianjin Yuan |
| collection | DOAJ |
| description | Substation equipment identification is a key step in the process of intelligent substation designing. The target recognition of 3D point cloud of substation equipment firstly uses a 3D laser scanner to obtain the 3D point cloud data that can express the surface shape and spatial position of a substation device, then identify the device information by matching it with template point cloud data. Because the point cloud data obtained by 3D laser scanner is affected by equipment attitude and substation environment, there is redundant, missing, and shadow phenomena in the data, resulting in a low algorithm recognition rate. This paper proposes a method combining plane detection and point cloud registration algorithm, achieving substation equipment identification better result. The main steps of the method include: point cloud preprocessing, plane detecting, preliminary filtering based on Umeyama registration method, and Iterative Closest Point (ICP) algorithm identifying. Plane detection is used for the pre-processed point cloud to obtain planar features, then samples and the planar feature templates in template library are preliminarily selected by Umeyama registration method, and substation equipment is finally identified by Iterative Closest Point algorithm. Experiments show that the recognition rate of devices point cloud reaches 92.2% and the recognition time is shorter, which proves that this recognition algorithm has a good recognition effect. |
| first_indexed | 2024-04-12T04:57:40Z |
| format | Article |
| id | doaj.art-10c6c957bc45411c965cf6a1ac6c3064 |
| institution | Directory Open Access Journal |
| issn | 2590-1230 |
| language | English |
| last_indexed | 2024-04-12T04:57:40Z |
| publishDate | 2022-09-01 |
| publisher | Elsevier |
| record_format | Article |
| series | Results in Engineering |
| spelling | doaj.art-10c6c957bc45411c965cf6a1ac6c30642022-12-22T03:47:04ZengElsevierResults in Engineering2590-12302022-09-01151005453D point cloud recognition of substation equipment based on plane detectionQianjin Yuan0Yong Luo1HeShan Wang2School of Electrical Engineering, Zhengzhou University, Zhengzhou, 450001, Henan, PR ChinaCorresponding author.; School of Electrical Engineering, Zhengzhou University, Zhengzhou, 450001, Henan, PR ChinaSchool of Electrical Engineering, Zhengzhou University, Zhengzhou, 450001, Henan, PR ChinaSubstation equipment identification is a key step in the process of intelligent substation designing. The target recognition of 3D point cloud of substation equipment firstly uses a 3D laser scanner to obtain the 3D point cloud data that can express the surface shape and spatial position of a substation device, then identify the device information by matching it with template point cloud data. Because the point cloud data obtained by 3D laser scanner is affected by equipment attitude and substation environment, there is redundant, missing, and shadow phenomena in the data, resulting in a low algorithm recognition rate. This paper proposes a method combining plane detection and point cloud registration algorithm, achieving substation equipment identification better result. The main steps of the method include: point cloud preprocessing, plane detecting, preliminary filtering based on Umeyama registration method, and Iterative Closest Point (ICP) algorithm identifying. Plane detection is used for the pre-processed point cloud to obtain planar features, then samples and the planar feature templates in template library are preliminarily selected by Umeyama registration method, and substation equipment is finally identified by Iterative Closest Point algorithm. Experiments show that the recognition rate of devices point cloud reaches 92.2% and the recognition time is shorter, which proves that this recognition algorithm has a good recognition effect.http://www.sciencedirect.com/science/article/pii/S2590123022002158Point cloudTarget recognitionSubstation equipmentRegistrationPlane detection |
| spellingShingle | Qianjin Yuan Yong Luo HeShan Wang 3D point cloud recognition of substation equipment based on plane detection Results in Engineering Point cloud Target recognition Substation equipment Registration Plane detection |
| title | 3D point cloud recognition of substation equipment based on plane detection |
| title_full | 3D point cloud recognition of substation equipment based on plane detection |
| title_fullStr | 3D point cloud recognition of substation equipment based on plane detection |
| title_full_unstemmed | 3D point cloud recognition of substation equipment based on plane detection |
| title_short | 3D point cloud recognition of substation equipment based on plane detection |
| title_sort | 3d point cloud recognition of substation equipment based on plane detection |
| topic | Point cloud Target recognition Substation equipment Registration Plane detection |
| url | http://www.sciencedirect.com/science/article/pii/S2590123022002158 |
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