矿震动载效应及冲击地压瞬态触发-连锁破坏机理  

Tremor dynamic loading effects and the transient triggering-linkage failure rockburst mechanism

作　　者：王桂峰[1] 陈烽 李宏维 曹安业[1] 石佳琦 静涛 窦林名[1] 温颖远 李庚 冯淦 WANG Guifeng;CHEN Feng;LI Hongwei;CAO Anye;SHI Jiaqi;JING Tao;DOU Linming;WEN Yingyuan;LI Geng;FENG Gan(State Key Laboratory for Fine Exploration and Intelligent Development of Coal Resources,School of Mines,China University of Mining and Technology,Xuzhou,Jiangsu 221116,China;School of Geology and Mining Engineering,Xinjiang University,Urumqi,Xinjiang 830046,China;China Mining Dingbei Technology(Xuzhou)Co Ltd,Xuzhou,Jiangsu 221116,China;College of Water Resource&Hydropower,Sichuan University,Chengdu,Sichuan 610065,China)

机构地区：[1]中国矿业大学煤炭精细勘探与智能开发全国重点实验室,矿业工程学院,江苏徐州221116 [2]新疆大学地质与矿业工程学院,新疆乌鲁木齐830000 [3]中矿鼎北科技(徐州)有限公司,江苏徐州221116 [4]四川大学水利水电学院,四川成都610065

出　　处：《采矿与安全工程学报》2025年第1期194-202,共9页Journal of Mining & Safety Engineering

基　　金：国家重点研发计划项目(2020YFB1314203,2020YFB1314204);山东能源科技计划重大项目(SNKJ2022A15);国家自然科学基金项目(51504248,52274098);江苏省自然科学基金项目(BK20140194);江苏省重点研发计划项目(BE2015040);国家自然科学基金重大科研仪器研制项目(52227901)。

摘　　要：由于冲击地压机理复杂、影响因素众多,到目前为止还未真正完全掌握其发生规律和发生机理。通过定量表征巷道围岩震动速度、应力状态和冲击破坏形态,系统研究了矿震动载作用下的巷道围岩动力响应特征和冲击破坏规律,建立了动静载瞬态触发-连锁破坏冲击模型,提出了基于机器学习模型的巷道抗冲能力智能评估技术。研究表明:矿震动载强度、其与巷道的距离、围岩自身静载应力、卸压工程及支护条件等均是影响巷道围岩发生冲击破坏的重要因素。动载强度较小时,巷道震动速度和底板位移小,未发生冲击破坏;动载强度增大到一定值后,巷道瞬间发生冲击破坏,且冲击破坏程度随动载强度增大而升高。采动、构造、煤柱等引发的巷道自身静载应力集中会减小其抗动载能力,相同动载作用下的巷道更容易发生冲击,且水平构造应力的影响更大。当构造导致的水平应力增大至1.5倍时,相同动载作用下的巷道由稳定转变为冲击破坏。围岩支护与卸压均会提高巷道冲击破坏的临界条件,避免巷道在同样动载荷作用下发生冲击。基于机器学习巷道抗冲能力评估模型的样本误差满足正态分布规律,表明模型评价指标选取合理,能够较好地反映巷道动力响应特征,对巷道震动速度和冲击情况预测的准确性高。研究成果在一定程度上促进了冲击地压机理研究,并为冲击地压防控提供了理论基础。The occurrence law and mechanism of rockburst have not yet been fully understood as they are complex and affected by multiple factors.By quantitatively characterizing the vibration velocity,stress state,and failure mode of roadways,the dynamic response characteristics and rockburst failure laws of roadways under tremor dynamic loads were systematically studied.On this basis,a transient triggering-linkage failure rockburst model was established,and the intelligent evaluation technology for the rockburst resistance capacity of roadway based on machine learning models was developed.The results suggest that dynamic load intensity,distance of dynamic load from roadways,static stress of surrounding rock,stress relief engineering,and roadway support are all important factors that determine whether the roadway surrounding rock can resist rockburst failure.When the dynamic load intensity is low,the roadway vibration speed and floor displacement are mild,and no rockburst failure occurs.After the dynamic load intensity rises to a certain value,rockburst failure will occur instantaneously,and the failure degree increases with the growth of dynamic loading strength.The static stress concentration of the roadway itself caused by mining activities,geological structures,and coal pillars would reduce its dynamic load resistance capacity,making it more prone to rockburst under the same dynamic load,and the influence of horizontal tectonic stress is even greater.When the horizontal tectonic stress increases by 1.5 times,the roadway starts to undergo rockburst failure under the same dynamic load.Roadway support and stress relief measures could both improve the critical condition for rockburst failure and contribute to avoiding rockburst under the same dynamic load.The sample errors of the rockburst resistance evaluation model based on machine learning models follow normal distribution,which indicates reasonableness of the selected evaluation indicators for the model.Additionally,this also means that the model can well reflect the dy

关 键 词：深部开采 矿震 冲击地压 动力响应 冲击机理 

分 类 号：P631[天文地球—地质矿产勘探]