School of Computer Science, North China Institute of Science and Technology, Beijing 101601, China.
School of Earth Sciences and Engineering, Nanjing University, Nanjing 210023, China.
Sensors (Basel). 2023 Jun 27;23(13):5947. doi: 10.3390/s23135947.
Underground coal mining can cause the deformation, failure, and collapse of the overlying rock mass of a coal seam. If the mining design, monitoring, early warning, or emergency disposal are improper, in that case, it can often lead to mining disasters such as roof falls, water inrush, surface collapse, and ground fissures, seriously threatening the safety of mine engineering and the geological environment protection in mining areas. To ensure the intrinsic security of the entire coal mining process, aspace-time continuous sensing system of overburden deformation and failure was developed, which breaks through the limitations of traditional monitoring methods that characterize the evolution process of overlying rock deformation and ground subsidence. This paper summarizes the classification of typical overburden deformation and failure modes. It researches the space-time continuous sensing of rock-soil mass above the coal seam based on Distributed Fiber Optic Sensing (DFOS). A multi-range strain optical fiber sensing neural series from micron to meter was developed to achieve synchronous sensing of overburden separation, internal micro-cracks, and large rock mass deformation. The sensing cable-rock mass coupling test verified the reliability of the optical fiber monitoring data. The sensing neural network of overburden deformation was constructed using integrated optical fiber layout technology on the ground and underground. Different sensing nerves' performance and application effects in overburden deformation and failure monitoring were compared and analyzed with field monitoring examples. A physical model was used to carry out the experimental study on the overburden subsidence prediction during coal mining. The results showed that the optical fiber monitoring data were reliable and could be used to predict overburden subsidence. The reliability of the calculation model for overlying rock subsidence based on space-time continuous optical fiber sensing data was verified in the application of mining subsidence evaluation. A systematic review of the shortcomings of current overburden deformation observation technology during coal mining was conducted, and a space-time continuous sensing system for overburden deformation and failure was proposed. This system integrated sensing, transmission, processing, early warning, decision-making, and emergency response. Based on the fusion of multi-parameter sensing, multi-method transmission, multi-algorithm processing, and multi-threshold early warning, the system realized the real-time acquisition of space-time continuous information for the overburden above coal seams. This system utilizes long-term historical monitoring data from the research area for data mining and modeling, realizing the prediction and evaluation of the evolution process of overburden deformation as well as the potential for mining subsidence. This work provides a theoretical reference for the prevention and control of mining disasters and the environmental carrying capacity evaluation of coal development.
地下采煤会导致煤层上方覆岩的变形、破坏和坍塌。如果采矿设计、监测、预警或应急处置不当,往往会导致冒顶、突水、地表塌陷、地裂缝等采矿灾害,严重威胁矿山工程安全和矿区地质环境安全。为确保整个采煤过程的固有安全性,开发了一种覆岩变形破坏的时空连续感知系统,突破了传统监测方法对覆岩变形和地面沉降演化过程的刻画局限。本文总结了典型覆岩变形破坏模式的分类,研究了基于分布式光纤传感(DFOS)的煤层上覆岩土体的时空连续感知。开发了从微米到米的多量程应变光纤传感神经系列,实现了覆岩离层、内部微裂缝和大岩体变形的同步感知。传感光缆-岩体耦合试验验证了光纤监测数据的可靠性。利用地面和地下集成光纤布局技术构建了覆岩变形的传感神经网络。通过现场监测实例,对比分析了不同传感神经在覆岩变形和破坏监测中的性能和应用效果。采用物理模型对采煤过程中的覆岩沉降进行了实验研究。结果表明,光纤监测数据可靠,可用于预测覆岩沉降。基于时空连续光纤传感数据的上覆岩层沉降预测计算模型在采煤沉降评价中的应用验证了该模型的可靠性。对当前采煤覆岩变形观测技术的缺点进行了系统的回顾,提出了一种覆岩变形破坏的时空连续感知系统。该系统集成了传感、传输、处理、预警、决策和应急响应。基于多参数传感融合、多方法传输、多算法处理和多阈值预警,实现了对煤层上方覆岩时空连续信息的实时获取。该系统利用研究区的长期历史监测数据进行数据挖掘和建模,实现了覆岩变形演化过程的预测和评价,以及采动沉降的潜力。本工作为采矿灾害防治和煤炭开发环境承载能力评价提供了理论参考。