Semi-automatic Identification of Tunnel Discontinuity Based on 3D Laser Scanning
Obtaining accurate discontinuity information on a tunnel is essential for tunnel stability assessment, and usually requires geological surveys on the tunnel surface. However, traditional manual measurement methods are time-consuming, labor-intensive, and provide limited data, particularly when deali...
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| Veröffentlicht in: | Geotechnical and geological engineering 2024-06, Vol.42 (4), p.2577-2599 |
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| creator | Chen, Na Xiao, Ao Li, Lihua Xiao, Henglin |
| description | Obtaining accurate discontinuity information on a tunnel is essential for tunnel stability assessment, and usually requires geological surveys on the tunnel surface. However, traditional manual measurement methods are time-consuming, labor-intensive, and provide limited data, particularly when dealing with complex tunnel rock masses. To address this problem, this paper proposes a method to quickly obtain the point cloud model of the tunnel surface and semi-automatically identify discontinuity using 3D laser scanner. The method is centered on an improved Regional Growth (RG) algorithm, with key principles and processing flow encompassing: (1) Voxel filtering; (2) Normal calculation for point clouds; (3) Improved RG algorithm; (4) Calculation of discontinuity orientation. An analysis of parametric sensitivity which proved its good robustness was carried out to assess the performance of the method. To ascertain the effectiveness of the method in semi-automatically identifying tunnel discontinuities, three sets of test data (standard cube, rock slope in Colorado, and Xulong hydroelectric station tunnel) were chosen. By comparing the analysis results of the proposed method with those of alternative methods (DSE and CloudCompare), the validation of its efficacy in tunnel discontinuity detection was achieved. |
| doi_str_mv | 10.1007/s10706-023-02692-2 |
| format | Article |
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However, traditional manual measurement methods are time-consuming, labor-intensive, and provide limited data, particularly when dealing with complex tunnel rock masses. To address this problem, this paper proposes a method to quickly obtain the point cloud model of the tunnel surface and semi-automatically identify discontinuity using 3D laser scanner. The method is centered on an improved Regional Growth (RG) algorithm, with key principles and processing flow encompassing: (1) Voxel filtering; (2) Normal calculation for point clouds; (3) Improved RG algorithm; (4) Calculation of discontinuity orientation. An analysis of parametric sensitivity which proved its good robustness was carried out to assess the performance of the method. To ascertain the effectiveness of the method in semi-automatically identifying tunnel discontinuities, three sets of test data (standard cube, rock slope in Colorado, and Xulong hydroelectric station tunnel) were chosen. By comparing the analysis results of the proposed method with those of alternative methods (DSE and CloudCompare), the validation of its efficacy in tunnel discontinuity detection was achieved.</description><identifier>ISSN: 0960-3182</identifier><identifier>EISSN: 1573-1529</identifier><identifier>DOI: 10.1007/s10706-023-02692-2</identifier><language>eng</language><publisher>Cham: Springer International Publishing</publisher><subject>Algorithms ; Automation ; Civil Engineering ; Discontinuity ; Earth and Environmental Science ; Earth Sciences ; Geological surveys ; Geology ; Geotechnical Engineering & Applied Earth Sciences ; Hydroelectric power ; Hydrogeology ; Laser applications ; Lasers ; Measurement methods ; Methods ; Original Paper ; Parameter sensitivity ; Performance assessment ; Rock masses ; Rocks ; Scanners ; Stability analysis ; Terrestrial Pollution ; Three dimensional models ; Tunnels ; Waste Management/Waste Technology</subject><ispartof>Geotechnical and geological engineering, 2024-06, Vol.42 (4), p.2577-2599</ispartof><rights>The Author(s), under exclusive licence to Springer Nature Switzerland AG 2023. 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However, traditional manual measurement methods are time-consuming, labor-intensive, and provide limited data, particularly when dealing with complex tunnel rock masses. To address this problem, this paper proposes a method to quickly obtain the point cloud model of the tunnel surface and semi-automatically identify discontinuity using 3D laser scanner. The method is centered on an improved Regional Growth (RG) algorithm, with key principles and processing flow encompassing: (1) Voxel filtering; (2) Normal calculation for point clouds; (3) Improved RG algorithm; (4) Calculation of discontinuity orientation. An analysis of parametric sensitivity which proved its good robustness was carried out to assess the performance of the method. To ascertain the effectiveness of the method in semi-automatically identifying tunnel discontinuities, three sets of test data (standard cube, rock slope in Colorado, and Xulong hydroelectric station tunnel) were chosen. By comparing the analysis results of the proposed method with those of alternative methods (DSE and CloudCompare), the validation of its efficacy in tunnel discontinuity detection was achieved.</description><subject>Algorithms</subject><subject>Automation</subject><subject>Civil Engineering</subject><subject>Discontinuity</subject><subject>Earth and Environmental Science</subject><subject>Earth Sciences</subject><subject>Geological surveys</subject><subject>Geology</subject><subject>Geotechnical Engineering & Applied Earth Sciences</subject><subject>Hydroelectric power</subject><subject>Hydrogeology</subject><subject>Laser applications</subject><subject>Lasers</subject><subject>Measurement methods</subject><subject>Methods</subject><subject>Original Paper</subject><subject>Parameter sensitivity</subject><subject>Performance assessment</subject><subject>Rock masses</subject><subject>Rocks</subject><subject>Scanners</subject><subject>Stability analysis</subject><subject>Terrestrial Pollution</subject><subject>Three dimensional models</subject><subject>Tunnels</subject><subject>Waste Management/Waste Technology</subject><issn>0960-3182</issn><issn>1573-1529</issn><fulltext>true</fulltext><rsrctype>article</rsrctype><creationdate>2024</creationdate><recordtype>article</recordtype><recordid>eNp9kE9LAzEQxYMoWKtfwFPAc3SS7Cabo9Z_hYJC6zmEzWxJabM12T302xut4M3DMDPM772BR8g1h1sOoO8yBw2KgZCllBFMnJAJr7VkvBbmlEzAKGCSN-KcXOS8ASgY8Al5X-IuMDcO_c4NoaVzj3EIXWjL1kfad3Q1xohb-hhy25dTHMNwoA8uo6cFkI90UeZEl62LMcT1JTnr3Dbj1W-fko_np9XslS3eXuaz-wVzwsiBOa3A-MojSvDaN6ZWSglUpkLUphKdERVqbpQDLzqHolWG-wYaqDuDopZTcnP03af-c8Q82E0_plheWglVLbUxShdKHKk29Tkn7Ow-hZ1LB8vBfidnj8nZkpz9Sc6KIpJHUS5wXGP6s_5H9QUnfm_g</recordid><startdate>20240601</startdate><enddate>20240601</enddate><creator>Chen, Na</creator><creator>Xiao, Ao</creator><creator>Li, Lihua</creator><creator>Xiao, Henglin</creator><general>Springer International Publishing</general><general>Springer Nature B.V</general><scope>AAYXX</scope><scope>CITATION</scope><scope>7TN</scope><scope>7UA</scope><scope>C1K</scope><scope>F1W</scope><scope>H96</scope><scope>L.G</scope><orcidid>https://orcid.org/0000-0001-5756-6257</orcidid></search><sort><creationdate>20240601</creationdate><title>Semi-automatic Identification of Tunnel Discontinuity Based on 3D Laser Scanning</title><author>Chen, Na ; Xiao, Ao ; Li, Lihua ; Xiao, Henglin</author></sort><facets><frbrtype>5</frbrtype><frbrgroupid>cdi_FETCH-LOGICAL-a293t-a7609d4dee30d7d8956662e694ee7942f924e7196a0d2fae2c691d80805f9e253</frbrgroupid><rsrctype>articles</rsrctype><prefilter>articles</prefilter><language>eng</language><creationdate>2024</creationdate><topic>Algorithms</topic><topic>Automation</topic><topic>Civil Engineering</topic><topic>Discontinuity</topic><topic>Earth and Environmental Science</topic><topic>Earth Sciences</topic><topic>Geological surveys</topic><topic>Geology</topic><topic>Geotechnical Engineering & Applied Earth Sciences</topic><topic>Hydroelectric power</topic><topic>Hydrogeology</topic><topic>Laser applications</topic><topic>Lasers</topic><topic>Measurement methods</topic><topic>Methods</topic><topic>Original Paper</topic><topic>Parameter sensitivity</topic><topic>Performance assessment</topic><topic>Rock masses</topic><topic>Rocks</topic><topic>Scanners</topic><topic>Stability analysis</topic><topic>Terrestrial Pollution</topic><topic>Three dimensional models</topic><topic>Tunnels</topic><topic>Waste Management/Waste Technology</topic><toplevel>peer_reviewed</toplevel><toplevel>online_resources</toplevel><creatorcontrib>Chen, Na</creatorcontrib><creatorcontrib>Xiao, Ao</creatorcontrib><creatorcontrib>Li, Lihua</creatorcontrib><creatorcontrib>Xiao, Henglin</creatorcontrib><collection>CrossRef</collection><collection>Oceanic Abstracts</collection><collection>Water Resources Abstracts</collection><collection>Environmental Sciences and Pollution Management</collection><collection>ASFA: Aquatic Sciences and Fisheries Abstracts</collection><collection>Aquatic Science & Fisheries Abstracts (ASFA) 2: Ocean Technology, Policy & Non-Living Resources</collection><collection>Aquatic Science & Fisheries Abstracts (ASFA) Professional</collection><jtitle>Geotechnical and geological engineering</jtitle></facets><delivery><delcategory>Remote Search Resource</delcategory><fulltext>fulltext</fulltext></delivery><addata><au>Chen, Na</au><au>Xiao, Ao</au><au>Li, Lihua</au><au>Xiao, Henglin</au><format>journal</format><genre>article</genre><ristype>JOUR</ristype><atitle>Semi-automatic Identification of Tunnel Discontinuity Based on 3D Laser Scanning</atitle><jtitle>Geotechnical and geological engineering</jtitle><stitle>Geotech Geol Eng</stitle><date>2024-06-01</date><risdate>2024</risdate><volume>42</volume><issue>4</issue><spage>2577</spage><epage>2599</epage><pages>2577-2599</pages><issn>0960-3182</issn><eissn>1573-1529</eissn><abstract>Obtaining accurate discontinuity information on a tunnel is essential for tunnel stability assessment, and usually requires geological surveys on the tunnel surface. However, traditional manual measurement methods are time-consuming, labor-intensive, and provide limited data, particularly when dealing with complex tunnel rock masses. To address this problem, this paper proposes a method to quickly obtain the point cloud model of the tunnel surface and semi-automatically identify discontinuity using 3D laser scanner. The method is centered on an improved Regional Growth (RG) algorithm, with key principles and processing flow encompassing: (1) Voxel filtering; (2) Normal calculation for point clouds; (3) Improved RG algorithm; (4) Calculation of discontinuity orientation. An analysis of parametric sensitivity which proved its good robustness was carried out to assess the performance of the method. To ascertain the effectiveness of the method in semi-automatically identifying tunnel discontinuities, three sets of test data (standard cube, rock slope in Colorado, and Xulong hydroelectric station tunnel) were chosen. 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| ispartof | Geotechnical and geological engineering, 2024-06, Vol.42 (4), p.2577-2599 |
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| subjects | Algorithms Automation Civil Engineering Discontinuity Earth and Environmental Science Earth Sciences Geological surveys Geology Geotechnical Engineering & Applied Earth Sciences Hydroelectric power Hydrogeology Laser applications Lasers Measurement methods Methods Original Paper Parameter sensitivity Performance assessment Rock masses Rocks Scanners Stability analysis Terrestrial Pollution Three dimensional models Tunnels Waste Management/Waste Technology |
| title | Semi-automatic Identification of Tunnel Discontinuity Based on 3D Laser Scanning |
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