中南大学学报（自然科学版）2024，Vol.55Issue(9)：3457-3468,12.DOI:10.11817/j.issn.1672-7207.2024.09.019
基于计算机视觉的深部软岩巷道变形破裂特征试验研究
Experimental study on deformation and fracture characteristics of deep soft rock roadway based on computer vision
摘要
Abstract
The large deformation of surrounding rock caused by roadway rupture is a difficult problem in the stability control of surrounding rock in deep coal mining.Aiming at the problem,the evolution characterization of bulking deformation in surrounding rock of deep roadway was investigated,a large-scale similarity model test was conducted and a self-developed computer vision measurement system was used for deformation of surrounding rock precise field measurement and rupture identification characterization.The results show that with the development and evolution of the number,length and area of cracks can be divided into radial crack development stage and ring crack development stage.Displacement changes of the surrounding rock exhibit inconsistency,the vertical displacement of the surrounding rock mass is mainly in the radial crack development stage,and the horizontal displacement of the surrounding rock mass is mainly in the ring crack development stage.Shear failure occurs in both supported and unsupported roadway sections under loading conditions.However,support structures effectively restrict mutual slip and dislocation among block of surrounding rock after shear failure,thereby reducing bulking deformation of roadway.The deformation and fracture evolution of the surrounding rock in deep roadway is manifested by the shear failure of the surrounding rock along the structural plane,resulting in radial cracks cutting the surrounding rock mass.As load increases,dislocation and slip of the surrounding rock mass lead to ring cracks formation and subsequent bulking deformation.关键词
深部巷道/模型试验/计算机视觉/碎胀变形/裂隙演化Key words
deep roadway/model test/computer vision/bulking deformation/evolution of crack分类
建筑与水利引用本文复制引用
赵万勇,李元海,于恒,徐晓华..基于计算机视觉的深部软岩巷道变形破裂特征试验研究[J].中南大学学报（自然科学版）,2024,55(9):3457-3468,12.基金项目
国家自然科学基金资助项目(52274141) （52274141）
国家重点研发项目(2022YFC3003304)(Project(52274141)supported （2022YFC3003304）
by the National Natural Science Foundation of China （）
Project(2022YFC3003304)supported by the National Key Research and Development Program of China) （2022YFC3003304）
