Li Zi-Qiang, Ma Gui-Quan, Zhou Ze-Lin, Zhang Jia-Shuai, Pu Sheng-Peng, Zheng Zi-Yi
School of Civil and Hydraulic Engineering, Chongqing University of Science and Technology, Chongqing, 401331, China.
China 19th Metallurgical Corporation, Chengdu, 610031, China.
Sci Rep. 2025 Aug 2;15(1):28257. doi: 10.1038/s41598-025-13682-0.
In this study, self-developed intelligent detection equipment was used to quickly detect the key parameters of peripheral eyes and scan the cross-section over-excavation based on the double-track tunnel project at Chongqing University Town. The correlation between the two was clarified using ANSYS/LS-DYNA finite element methods and then, the blasting drilling scheme was optimized. Three-dimensional imaging technology Integrated with high-precision laser scanning and an intelligent positioning system, is employed to acquire precise data regarding the excavation of the cross-section. The three-dimensional imaging technology intuitively represents the actual outline of the surrounding rock by creating a three-dimensional model of the tunnel excavation cross-section. The intelligent positioning system tracks the spatial coordinates of the blasthole in real time to ensure the accuracy of the position parameters of the peripheral eye. The results show that the positional deviation of the borehole in the perimeter eye can lead to significant over-excavation of the tunnel section, especially in the tunnel top and shoulder area. The field data show that when the average position deviation range of peripheral eyes is 17-23 cm, the over-excavation circumference of the tunnel measures 25.55-35.39 cm. The numerical simulation shows that the over-excavation caused by the spatial position deviation of the peripheral eye is approximately 2-3 times more than that caused by angular deviation, with average over-excavation in the top and shoulder areas of the tunnel reaching 45 cm and 18 cm, respectively. By implementing an optimized drilling strategy, the position deviation can be reduced to within 10 cm and the angular control can be improved, hence reducing the average over-excavation to 5 cm. The result serves as a benchmark for the further development of intelligent tunnel construction technology and the optimization of blasting construction under similar geological conditions.
在本研究中，基于重庆大学城的双轨隧道项目，使用自行研发的智能检测设备快速检测周边眼的关键参数，并扫描横断面超挖情况。利用ANSYS/LS-DYNA有限元方法阐明了两者之间的相关性，进而优化了爆破钻孔方案。采用集成高精度激光扫描和智能定位系统的三维成像技术，获取横断面开挖的精确数据。三维成像技术通过创建隧道开挖横断面的三维模型，直观地呈现了围岩的实际轮廓。智能定位系统实时跟踪炮孔的空间坐标，以确保周边眼位置参数的准确性。结果表明，周边眼中炮孔的位置偏差会导致隧道断面出现显著超挖，尤其是在隧道顶部和肩部区域。现场数据显示，当周边眼平均位置偏差范围为17 - 23厘米时，隧道超挖周长为25.55 - 35.39厘米。数值模拟表明，周边眼空间位置偏差引起的超挖量比角度偏差引起的超挖量大约多2 - 3倍，隧道顶部和肩部区域的平均超挖量分别达到45厘米和18厘米。通过实施优化的钻孔策略，位置偏差可降至10厘米以内，角度控制得到改善，从而将平均超挖量降至5厘米。该结果为智能隧道施工技术的进一步发展以及类似地质条件下爆破施工的优化提供了基准。
