2D–3D Geological features collaborative identification of surrounding rock structural planes in hydraulic adit based on OC-AINet
Timely acquisition of geological structure information is crucial for large-scale water conservancy and hydropower projects. Understanding surrounding rock structure is critical for rock deformation analysis and geological evaluation of hydraulic adits. This study proposes a new method of OC-AINet t...
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| Format: | Article |
| Language: | English |
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De Gruyter
2025-06-01
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| Series: | Open Geosciences |
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| Online Access: | https://doi.org/10.1515/geo-2025-0815 |
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| author | Yang Kaiji Zhang Rongchun Chen Yixiang Yi Xuefeng Wang Dongchuan Zhao Wenchao Wang Guogang Liu Lanfa Han Jiaqi |
| author_facet | Yang Kaiji Zhang Rongchun Chen Yixiang Yi Xuefeng Wang Dongchuan Zhao Wenchao Wang Guogang Liu Lanfa Han Jiaqi |
| author_sort | Yang Kaiji |
| collection | DOAJ |
| description | Timely acquisition of geological structure information is crucial for large-scale water conservancy and hydropower projects. Understanding surrounding rock structure is critical for rock deformation analysis and geological evaluation of hydraulic adits. This study proposes a new method of OC-AINet to achieve efficient and accurate recognition of geological structure information of large hydraulic adits. An ordinary digital camera is used to obtain images of the Heishanxia adit, and dense point clouds are generated through multi-view stereo reconstruction. 2D–3D feature semantic super-pixel blocks are segmented by combining color, texture, and other geological semantics with AINet, and then a hierarchical regional clustering is carried out for rock structural planes extraction. The experimental results show that the difference between the rock structural plane identification error of the proposed method and that of the traditional manual method is less than 5 degrees, which meets the requirements of geological analysis. In addition, it has higher efficiency and safety than the manual method. The proposed OC-AINet has significantly improved the accuracy and reliability of the segmentation results and promotes the application of photogrammetry technology in geological scenes, especially in hydraulic adit environments. |
| format | Article |
| id | doaj-art-3e180792eeec41f18583bd229b0c6d8e |
| institution | OA Journals |
| issn | 2391-5447 |
| language | English |
| publishDate | 2025-06-01 |
| publisher | De Gruyter |
| record_format | Article |
| series | Open Geosciences |
| spelling | doaj-art-3e180792eeec41f18583bd229b0c6d8e2025-08-20T02:06:47ZengDe GruyterOpen Geosciences2391-54472025-06-01171301810.1515/geo-2025-08152D–3D Geological features collaborative identification of surrounding rock structural planes in hydraulic adit based on OC-AINetYang Kaiji0Zhang Rongchun1Chen Yixiang2Yi Xuefeng3Wang Dongchuan4Zhao Wenchao5Wang Guogang6Liu Lanfa7Han Jiaqi8School of Geology and Geomatics, Tianjin Chengjian University, Tianjin, 300384, ChinaSchool of Geology and Geomatics, Tianjin Chengjian University, Tianjin, 300384, ChinaSchool of Internet of Things, Nanjing University of Posts and Telecommunications, Nanjing, 210023, ChinaChina Water Resources Bei Fang Investigation, Design & Research CO. LTD, Tianjin, 300222, ChinaSchool of Geology and Geomatics, Tianjin Chengjian University, Tianjin, 300384, ChinaChina Water Resources Bei Fang Investigation, Design & Research CO. LTD, Tianjin, 300222, ChinaChina Water Resources Bei Fang Investigation, Design & Research CO. LTD, Tianjin, 300222, ChinaCollege of Urban and Environmental Sciences, Central China Normal University, Wuhan, 430079, ChinaSchool of Internet of Things, Nanjing University of Posts and Telecommunications, Nanjing, 210023, ChinaTimely acquisition of geological structure information is crucial for large-scale water conservancy and hydropower projects. Understanding surrounding rock structure is critical for rock deformation analysis and geological evaluation of hydraulic adits. This study proposes a new method of OC-AINet to achieve efficient and accurate recognition of geological structure information of large hydraulic adits. An ordinary digital camera is used to obtain images of the Heishanxia adit, and dense point clouds are generated through multi-view stereo reconstruction. 2D–3D feature semantic super-pixel blocks are segmented by combining color, texture, and other geological semantics with AINet, and then a hierarchical regional clustering is carried out for rock structural planes extraction. The experimental results show that the difference between the rock structural plane identification error of the proposed method and that of the traditional manual method is less than 5 degrees, which meets the requirements of geological analysis. In addition, it has higher efficiency and safety than the manual method. The proposed OC-AINet has significantly improved the accuracy and reliability of the segmentation results and promotes the application of photogrammetry technology in geological scenes, especially in hydraulic adit environments.https://doi.org/10.1515/geo-2025-0815photogrammetrymulti-dimensional semantic fusionsuper-pixel segmentationstructural planeoccurrence |
| spellingShingle | Yang Kaiji Zhang Rongchun Chen Yixiang Yi Xuefeng Wang Dongchuan Zhao Wenchao Wang Guogang Liu Lanfa Han Jiaqi 2D–3D Geological features collaborative identification of surrounding rock structural planes in hydraulic adit based on OC-AINet Open Geosciences photogrammetry multi-dimensional semantic fusion super-pixel segmentation structural plane occurrence |
| title | 2D–3D Geological features collaborative identification of surrounding rock structural planes in hydraulic adit based on OC-AINet |
| title_full | 2D–3D Geological features collaborative identification of surrounding rock structural planes in hydraulic adit based on OC-AINet |
| title_fullStr | 2D–3D Geological features collaborative identification of surrounding rock structural planes in hydraulic adit based on OC-AINet |
| title_full_unstemmed | 2D–3D Geological features collaborative identification of surrounding rock structural planes in hydraulic adit based on OC-AINet |
| title_short | 2D–3D Geological features collaborative identification of surrounding rock structural planes in hydraulic adit based on OC-AINet |
| title_sort | 2d 3d geological features collaborative identification of surrounding rock structural planes in hydraulic adit based on oc ainet |
| topic | photogrammetry multi-dimensional semantic fusion super-pixel segmentation structural plane occurrence |
| url | https://doi.org/10.1515/geo-2025-0815 |
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