基于采动岩体大数据的围岩损伤及失稳控制机理研究

With the metal mines go deeper, the mining-induced disasters (such as rock bursts) become more and more. The occurrence of the dynamic hazards is originally resulted from the damage and failure instability of rockmass. This project aims to investigate the country rock damage and ground control mechanism by mining the big data produced during real-time monitoring and numerical simulation for mining-disturbed rockmass. Firstly, the rockmass structure and mining-induced damage are characterized, and the method for characterizing mechanical parameters and damage variable of rock mass is established based on the big monitoring data. Secondly, the mechanical models of multi-strain rates and joint instability sliding are studied and proposed, and the numerical simulation tool for the damage and failure of rockmass is developed based on the cloud computing platform, based on which, the time effect and precursory information of rock burst triggered by mining disturbance are revealed. Lastly, on the basis of the cloud computing analysis of catastrophic process induced by the damage and failure of rockmass, the big data produced by the field monitoring and the cloud computing are mined, and the definitive links between the dominant hazard factors and early-warning index are discovered, in order to confirm the information sources and index system for early-warning of unstable failure of country rockmass. Combined the big monitoring data and cloud computing analysis, an approach to forecasting rock burst is developed further, and the mechanical mechanism for controlling rock burst by distressing and support measures is clarified. This study may provide theoretical and technological basis for safe and high-efficiency mining.

随着金属矿山逐步转入深部开采，岩爆等矿山动力灾害凸显。岩石损伤与破裂失稳是岩爆等矿山动力灾害发生的根源。本研究对采动岩体进行实时监测和计算分析所产生的大数据进行挖掘，以期揭示采动围岩损伤及地压控制的机理。首先，开展岩体结构与采动岩体损伤的表征，建立基于监测大数据的围岩参数及损伤的表征方法；然后，研究建立岩石损伤的多应变率模型和节理面失稳滑移力学模型，研发基于云计算的岩体损伤与破裂数值模拟系统，揭示开采扰动触发岩爆的时间效应及其前兆规律；最后，以开采诱发围岩损伤与破裂的致灾过程云计算分析为基础，对围岩监测大数据和云计算输出的计算大数据进行挖掘，揭示致灾主控因素与预警指标体系之间的确定性联系，确立矿山围岩破坏预警的信息源与指标体系；进一步发展监测大数据与岩体响应云计算分析相结合的岩爆分析预警方法，揭示通过卸压和支护等手段进行岩爆解危和防控的力学机理，为矿山安全高效开采提供理论与技术支撑。

开采扰动下岩体将会产生海量力学响应数据，挖掘海量力学响应数据与开采扰动及岩体损伤规律的关系是灾害预测预警的重要基础。本研究以揭示围岩损伤及失稳控制机理为目标，首先，基于倾斜摄影测量技术进行地表模型精细化重构，通过钻孔岩芯图像识别对岩体质量空间变异性进行表征，结合多源数据形成矿山精细化虚拟现实模型及数值模型；其次，进行动态扰动后岩石蠕变冲击实验，揭示动态扰动下岩石损伤劣化机理，基于此采用数值模拟的方式，对动态扰动下边坡、空区稳定性进行数值模拟分析；再次，开展监测大数据与云计算分析相结合的灾害预警方法研究，以多源异构监测大数据实时采集及云端融合技术为获取数据的基础，提出多元监测大数据挖掘的灾害预测算法及现场监测和数值模拟相结合的灾害预测预警方法，实现了灾害的超前预测预警；最后，提出基于岩体损伤大数据的围岩控制机理与设计理念，揭示了围岩大变形及其控制机理、锚固岩体变形机理，搭建了“四位一体”地质灾害监测预警云平台以及基于混合现实技术的爆破后井下采场环境感知试验平台，相关成果已应用至国内众多矿山，为矿山的生产安全提供保障。