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MODERN TUNNELLING TECHNOLOGY 2025, Vol. 62 Issue (2) :87-97    DOI:
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Research on Construction and Application of a Rapid Tunnel Surrounding Rock Classification Model Based on Real-time Images and Advanced Geological Information
(1. School of Civil Engineering, Xi′an University of Architecture and Technology, Xi′an 710055; 2. Shanxi Key Laboratory of Geotechnical and Underground Space Engineering, Xi′an 710055; 3. Institute of Intelligent Construction of Infrastructure, College of Intersection and Future, Xi ′an University of Architecture and Technology, Xi′an 710055; 4. China Railway Construction Kunlun Investment Group Co., Ltd., Chengdu 610095; 5. Shaanxi Yinhan Jiwei Engineering Construction Co., Ltd., Xi ′an 710024)
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Abstract To accurately determine the surrounding rock grade of a tunnel, it is essential to conduct real-time, rapid, and objective evaluations of the tunnel excavation face and perform proactive rock mass risk assessments. Based on the Jianhe-Liping Expressway project in Guizhou, a rapid classification system for surrounding rock is established using basic rock mass quality indicators. During construction, image recognition, target detection, and image threshold segmentation technologies are used to quickly capture the joint information and weathering degree of the tunnel excavation face. Combined with seismic wave velocity and waveform diagrams from advanced geological prediction,surrounding rock parameters, rock integrity, and the development of joints and fractures are obtained. A Mamdani fuzzy inference system (FIS) is introduced, with both qualitative descriptions and quantitative parameters of surrounding rock as inputs to the evaluation information. This system is used to build a rapid real-time dynamic classification model for surrounding rock during the construction phase. The study shows that the model can integrate realtime tunnel excavation face images and advanced geological prediction data to monitor the surrounding rock condition at the tunnel excavation face in real-time, quickly responding to geological changes. The model classification results can provide a basis for adjusting construction strategies in a timely manner.
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ZHANG Meining1
2 SONG Zhanping1
2
3 YUE Bo4 LI Xu1
2
3 ZHAO Yirui2 TAO Lei5
KeywordsTunnel engineering   Surrounding rock classification   Real-time images   Deep learning   Advanced geo? logical prediction   Fuzzy inference     
Abstract: To accurately determine the surrounding rock grade of a tunnel, it is essential to conduct real-time, rapid, and objective evaluations of the tunnel excavation face and perform proactive rock mass risk assessments. Based on the Jianhe-Liping Expressway project in Guizhou, a rapid classification system for surrounding rock is established using basic rock mass quality indicators. During construction, image recognition, target detection, and image threshold segmentation technologies are used to quickly capture the joint information and weathering degree of the tunnel excavation face. Combined with seismic wave velocity and waveform diagrams from advanced geological prediction,surrounding rock parameters, rock integrity, and the development of joints and fractures are obtained. A Mamdani fuzzy inference system (FIS) is introduced, with both qualitative descriptions and quantitative parameters of surrounding rock as inputs to the evaluation information. This system is used to build a rapid real-time dynamic classification model for surrounding rock during the construction phase. The study shows that the model can integrate realtime tunnel excavation face images and advanced geological prediction data to monitor the surrounding rock condition at the tunnel excavation face in real-time, quickly responding to geological changes. The model classification results can provide a basis for adjusting construction strategies in a timely manner.
KeywordsTunnel engineering,   Surrounding rock classification,   Real-time images,   Deep learning,   Advanced geo? logical prediction,   Fuzzy inference     
Cite this article:   
ZHANG Meining1, 2 SONG Zhanping1, 2 etc .Research on Construction and Application of a Rapid Tunnel Surrounding Rock Classification Model Based on Real-time Images and Advanced Geological Information[J]  MODERN TUNNELLING TECHNOLOGY, 2025,V62(2): 87-97
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