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隧道建设(中英文) ›› 2024, Vol. 44 ›› Issue (5): 964-972.DOI: 10.3973/j.issn.2096-4498.2024.05.005

• 研究与探索 • 上一篇    下一篇

基于图像识别的TBM隧道围岩条件与岩渣级配相关性研究

周振梁1, 雷可1, 李庆楼1, *, 肖海晖2, 苏珊3   

  1. 1. 北京交通大学 城市地下工程教育部重点实验室, 北京 100044 2. 中铁十六局集团有限公司, 北京 101499; 3. 新疆水利发展投资(集团)有限公司, 新疆 乌鲁木齐 830000)

  • 出版日期:2024-05-20 发布日期:2024-06-22
  • 作者简介:周振梁(1994—),男,山西忻州人,2022年毕业于北京交通大学,土木工程专业,博士,讲师,主要从事隧道及地下工程方面的教学与研究工作。Email: zlzhou1@bjtu.edu.cn。*通信作者: 李庆楼, Email: 22110338@bjtu.edu.cn。

Correlation Between Surrounding Rock Conditions and RockSlag Grading of Tunnels Bored Using Tunnel Boring Machines Via Image Recognition

ZHOU Zhenliang1, LEI Ke1, LI Qinglou1, *, XIAO Haihui2, SU Shan3   

  1. (1. Key Laboratory for Urban Underground Engineering of Ministry of Education, Beijing Jiaotong University, Beijing 100044, China; 2. China Railway 16th Bureau Group Corporation Limited, Beijing 101499, China; 3. Xinjiang Water Conservancy Development Investment (Group) Co., Ltd., Urumqi 830000, Xinjiang, China)
  • Online:2024-05-20 Published:2024-06-22

摘要: 为了在TBM不停机的条件下根据岩渣特征提前判断掌子面围岩条件,建立TBM岩渣图像采集系统,对各类围岩条件下产生的渣片图像进行采集,借助二值化与分水岭分割方法对渣片图像进行处理,选取曲率系数、不均匀系数、最大粒径和粗糙度指数作为岩渣的级配特征指标,分别采用线性、对数、逆、二次、幂、复合、S曲线和增长共8种模型建立岩渣级配参数与围岩类别、岩石单轴抗压强度、岩石完整性系数之间的关系。结果表明: 1)随着围岩条件变差,岩渣的曲率系数逐渐减小,不均匀系数、最大粒径、粗糙度指数逐渐增大; 2)随着岩石单轴抗压强度增大,岩渣的曲率系数呈增大趋势,不均匀系数、最大粒径、粗糙度指数呈减小趋势; 3)随岩石完整性系数增加,岩渣曲率系数呈增大趋势,不均匀系数、最大粒径、粗糙度指数呈减小趋势。

关键词: TBM, 渣片识别, 图像采集系统, 图像处理, 级配特征参数 

Abstract: A slagimage acquisition system of tunnel boring machines(TBMs) is developed herein to predict the surrounding rock conditions at the excavation face in advance based on the characteristics of rock slag without halting the TBM. Slag images are captured under various surrounding rock conditions and processed using binarization and watershed segmentation methods. The curvature coefficient, nonuniformity coefficient, maximum particle size, and roughness index are used as slag grading characteristic indices. Eight models, namely linear, logarithmic, inverse, quadratic, power, compound, Scurve, and growth, are employed to establish relationships among rockslag grading parameters and the types, uniaxial compressive strengths, and integrity coefficients of surrounding rocks. The results indicate the following: (1) The curvature coefficient of slag decreases while the nonuniformity coefficient, maximum particle size, and roughness index increase as surrounding rock conditions deteriorate. (2) The curvature coefficient of rock slag increases while the nonuniformity coefficient, maximum particle size, and roughness index decrease with increasing uniaxial compressive strength of rock. (3) The curvature coefficient of rock slag increases while the nonuniformity coefficient, maximum particle size, and roughness index decrease with increasing rock integrity coefficient.

Key words: tunnel boring machine, slag identification, image acquisition system, image processing, gradation characteristic parameter