A Coal Mine Tunnel Deformation Detection Method Using Point Cloud Data
In recent years, the deformation detection technology for underground tunnels has played a crucial role in coal mine safety management. Currently, traditional methods such as the cross method and those employing the roof abscission layer monitoring instrument are primarily used for tunnel deformatio...
| Main Authors: | , , , , , |
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| Format: | Article |
| Language: | English |
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MDPI AG
2024-04-01
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| Series: | Sensors |
| Subjects: | |
| Online Access: | https://www.mdpi.com/1424-8220/24/7/2299 |
| _version_ | 1797211962945306624 |
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| author | Jitong Kang Mei Li Shanjun Mao Yingbo Fan Zheng Wu Ben Li |
| author_facet | Jitong Kang Mei Li Shanjun Mao Yingbo Fan Zheng Wu Ben Li |
| author_sort | Jitong Kang |
| collection | DOAJ |
| description | In recent years, the deformation detection technology for underground tunnels has played a crucial role in coal mine safety management. Currently, traditional methods such as the cross method and those employing the roof abscission layer monitoring instrument are primarily used for tunnel deformation detection in coal mines. With the advancement of photogrammetric methods, three-dimensional laser scanners have gradually become the primary method for deformation detection of coal mine tunnels. However, due to the high-risk confined spaces and distant distribution of coal mine tunnels, stationary three-dimensional laser scanning technology requires a significant amount of labor and time, posing certain operational risks. Currently, mobile laser scanning has become a popular method for coal mine tunnel deformation detection. This paper proposes a method for detecting point cloud deformation of underground coal mine tunnels based on a handheld three-dimensional laser scanner. This method utilizes SLAM laser radar to obtain complete point cloud information of the entire tunnel, while projecting the three-dimensional point cloud onto different planes to obtain the coordinates of the tunnel centerline. By using the calculated tunnel centerline, the three-dimensional point cloud data collected at different times are matched to the same coordinate system, and then the tunnel deformation parameters are analyzed separately from the global and cross-sectional perspectives. Through on-site collection of tunnel data, this paper verifies the feasibility of the algorithm and compares it with other centerline fitting and point cloud registration algorithms, demonstrating higher accuracy and meeting practical needs. |
| first_indexed | 2024-04-24T10:34:50Z |
| format | Article |
| id | doaj.art-a7d026be116d42bab582c5572a4b8e93 |
| institution | Directory Open Access Journal |
| issn | 1424-8220 |
| language | English |
| last_indexed | 2024-04-24T10:34:50Z |
| publishDate | 2024-04-01 |
| publisher | MDPI AG |
| record_format | Article |
| series | Sensors |
| spelling | doaj.art-a7d026be116d42bab582c5572a4b8e932024-04-12T13:26:43ZengMDPI AGSensors1424-82202024-04-01247229910.3390/s24072299A Coal Mine Tunnel Deformation Detection Method Using Point Cloud DataJitong Kang0Mei Li1Shanjun Mao2Yingbo Fan3Zheng Wu4Ben Li5Institute of Remote Sensing and Geographic Information System, Peking University, Beijing 100871, ChinaInstitute of Remote Sensing and Geographic Information System, Peking University, Beijing 100871, ChinaInstitute of Remote Sensing and Geographic Information System, Peking University, Beijing 100871, ChinaInstitute of Remote Sensing and Geographic Information System, Peking University, Beijing 100871, ChinaInstitute of Remote Sensing and Geographic Information System, Peking University, Beijing 100871, ChinaInstitute of Remote Sensing and Geographic Information System, Peking University, Beijing 100871, ChinaIn recent years, the deformation detection technology for underground tunnels has played a crucial role in coal mine safety management. Currently, traditional methods such as the cross method and those employing the roof abscission layer monitoring instrument are primarily used for tunnel deformation detection in coal mines. With the advancement of photogrammetric methods, three-dimensional laser scanners have gradually become the primary method for deformation detection of coal mine tunnels. However, due to the high-risk confined spaces and distant distribution of coal mine tunnels, stationary three-dimensional laser scanning technology requires a significant amount of labor and time, posing certain operational risks. Currently, mobile laser scanning has become a popular method for coal mine tunnel deformation detection. This paper proposes a method for detecting point cloud deformation of underground coal mine tunnels based on a handheld three-dimensional laser scanner. This method utilizes SLAM laser radar to obtain complete point cloud information of the entire tunnel, while projecting the three-dimensional point cloud onto different planes to obtain the coordinates of the tunnel centerline. By using the calculated tunnel centerline, the three-dimensional point cloud data collected at different times are matched to the same coordinate system, and then the tunnel deformation parameters are analyzed separately from the global and cross-sectional perspectives. Through on-site collection of tunnel data, this paper verifies the feasibility of the algorithm and compares it with other centerline fitting and point cloud registration algorithms, demonstrating higher accuracy and meeting practical needs.https://www.mdpi.com/1424-8220/24/7/2299point cloudunderground tunnelcoal minedeformation detection |
| spellingShingle | Jitong Kang Mei Li Shanjun Mao Yingbo Fan Zheng Wu Ben Li A Coal Mine Tunnel Deformation Detection Method Using Point Cloud Data Sensors point cloud underground tunnel coal mine deformation detection |
| title | A Coal Mine Tunnel Deformation Detection Method Using Point Cloud Data |
| title_full | A Coal Mine Tunnel Deformation Detection Method Using Point Cloud Data |
| title_fullStr | A Coal Mine Tunnel Deformation Detection Method Using Point Cloud Data |
| title_full_unstemmed | A Coal Mine Tunnel Deformation Detection Method Using Point Cloud Data |
| title_short | A Coal Mine Tunnel Deformation Detection Method Using Point Cloud Data |
| title_sort | coal mine tunnel deformation detection method using point cloud data |
| topic | point cloud underground tunnel coal mine deformation detection |
| url | https://www.mdpi.com/1424-8220/24/7/2299 |
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