煤炭资源在我国经济发展中占据着主导地位，随着国民经济的快速发展，对于煤炭需求量日益增加。但是大规模开采会给矿区及周边带来一系列地质灾害，使得矿区人民生命安全受到严重威胁。为了减少开采沉陷对矿区环境的破坏力度，对矿区地表形变进行实时监测和预测非常必要。目前，矿区地表形变监测技术有很多，合成孔径雷达干涉测量（Interferometry Synthetic Aperture Radar, InSAR）技术作为一种新型的对地观测技术，在地表形变监测具有范围广、全天时、全天候等优势，相比于传统监测技术克服了监测周期长、受天气影响、范围小等缺点，因此在矿区地表形变监测中得到了广泛应用。所以如何实现矿区沉降监测和预测一体化，是当前地质灾害防治研究的热点。常用的预测方法虽然可以反应矿区某些区域未来的地表形变趋势，但是不能获取到矿区地表的动态变化过程，针对这个问题，本文主要是将SBAS-InSAR技术和PSO-SVR算法相结合对地表形变进行监测分析和预计研究，为矿区地质灾害预警提供了理论基础。最后运用FLAC 3D建立了紧邻工作面开采沉陷预测模型，对单一工作面和紧邻工作面开采进行了数值模拟，探究了工作面在不同推进距离下上覆岩层的变化特征和地表形变规律。主要研究内容如下：

（1）针对孟村矿区紧邻工作面开采条件下地表沉陷规律复杂问题，以矿区401101工作面和401102工作面为研究对象，利用SBAS-InSAR技术对覆盖孟村矿区的128景Sentinel-1A数据处理，获取到两个工作面年均沉降速率和地表时序累积沉降量。结合矿区资料从点、线、面等多个角度对地表形变特征进行分析。结果表明：地表沉陷结果在时间和空间和工作面分布位置有着良好的一致性，随着工作面的不断推进，地表沉降值和沉降速率逐渐增大。由于受紧邻工作面401102开采影响，401101工作面的下沉范围表现明显增加的趋势，地表沉陷出现了非对称特征，且靠近采空区越近的区域地表沉降值越大，沉降中心逐渐向采空区的一侧偏移。接着以GPS实测数据作为参考，利用修正模型对沉降结果修正，两者的决定系数达到了0.94，说明修正后结果可靠。

（2）针对传统开采沉陷预测方法的缺陷和预测精度较低的问题，本文基于SBAS-InSAR的监测结果和SVR算法、PSO-SVR算法相结合构建开采沉陷预计模型对矿区形变进行预测，在工作面上选取4个下沉趋势较为明显的特征点，提取出在2018年6月4日-2018年12月25日期间18期地表时序累积沉降量，以1-15期数据作为训练集，16-18期数据作为测试集。利用均方根误差(RMSE)、平均绝对误差（MAE）和决定系数（R²）作为预测结果精度评价指标。结果表明：PSO-SVR预测模型的平均绝对误差和均方根误差相比SVR预测模型较小，决定系数达到了0.9，并将两者预测结果和SBAS-InSAR结果对比分析，得知PSO-SVR模型在解决较为复杂的非线性问题时学习能力更强，预测结果稳定性更高。

（3）针对孟村矿区工作面煤层开采地表岩移规律的特殊性，根据孟村煤矿地质采矿条件建立了开采沉陷预测模型模拟并分析了工作面在不同推进距离下覆岩与地表岩移规律变化，并结合形变理论和数值模拟实验分析。研究表明：随着工作面的推进，采空区范围逐步增大，当采空区对地表影响增大到一定程度后地表发生沉陷及变形。地表产生最大下沉点处均在采空区上方中央位置，并且下沉曲线关于采空区中央最大下沉点对称，在不同推进长度下，越远离采空区中央上方，地表沉降越不明显。然而紧邻工作面开采与近水平煤层单一工作面开采沉陷所表现出的对称性特征不同，在老采空区影响下，地表下沉关于采空区中心呈非对称分布，靠近老采空区一侧沉陷变形量和变形剧烈程度明显大于未采区一侧，沉降中心会向老采空区方向偏移。

Coal resources occupy a dominant position in China's economic development, and with the rapid development of the national economy, the demand for coal is increasing. However, large-scale mining will bring a series of geological disasters to the mining area and the surrounding area, which will seriously threaten the life and safety of the people in the mining area. In order to reduce the damage of mining subsidence to the mining environment, it is very necessary to monitor and predict the surface deformation of the mining area in real time. At present, there are many surface deformation monitoring technologies in mining area, InSAR technology, as a new type of earth observation technology, has the advantages of wide range, all-day, all-weather in surface deformation monitoring, compared with the traditional monitoring technology to overcome the shortcomings of the monitoring cycle is long, affected by the weather, the range is small, and so on, so it is widely used in the monitoring of surface deformation in mining area. Therefore, how to achieve the integration of monitoring and prediction of mine subsidence is the hot spot of current research on prevention and control of geological disasters. Although the commonly used prediction methods can respond to the future surface deformation trend of some areas in the mining area, but they cannot obtain the dynamic change process of the surface in the mining area, to address this problem, this paper mainly combines the SBAS-InSAR technology and PSO-SVR algorithms to monitor and analyse and anticipate the research of surface deformation, which provides a theoretical basis for the early warning of geological hazards in the mining area. Finally, a prediction model of mining subsidence in the immediate working face was established by using FLAC 3D, and numerical simulation of single working face and immediate working face mining was carried out to explore the change characteristics of the overlying rock layer and the surface deformation law of the working face under different advancing distances. The main research contents are as follows:

(1)  Aiming at the complexity of the surface subsidence pattern under the mining conditions of the immediately neighbouring workings in the Mengcun mine area, we took the 401101 workings and 401102 workings in the mine area as the research objects, and processed the 128 views of Sentinel-1A data covering the Mengcun mine area with SBAS-InSAR technology, and obtained the annual average rate of the two workings and the time-sequence cumulative subsidence of the ground surface. The surface deformation characteristics were analysed from multiple perspectives, such as point, line and surface, in combination with the mine site data. The results show that the surface subsidence results have good consistency in time and space and the distribution location of the working face, and the surface subsidence value and subsidence rate gradually increase with the continuous advancement of the working face. Due to the influence of the mining of the adjacent working face 401102, the subsidence range of working face 401101 shows a significant increase in the trend, the surface subsidence appears asymmetric characteristics, and the closer the surface subsidence value of the area near the mining area is larger, and the centre of the subsidence is gradually shifted to the side of the mining area. Then, the GPS measured data were used as the reference, and the subsidence results were corrected by the correction model, and the coefficient of determination between the two reached 0.94, indicating that the corrected results were reliable.

(2)  Aiming at the defects of traditional mining subsidence prediction methods and the problem of low prediction accuracy, this paper constructs a mining subsidence prediction model based on the monitoring results of SBAS-InSAR and the combination of SVR algorithm and PSO-SVR algorithm to predict the deformation of the mining area, and selects four feature points on the workings with a more pronounced trend of subsidence, and extracts the cumulative subsidence of the ground surface in the period of 4 June 2018-25 December 2018, with the data of periods 1-15 as the training set and the data of periods 16-18 as the test set. During the period from 4 June 2018 to 25 December 2018, 18 periods of time-series cumulative subsidence of the surface were extracted, with the data of periods 1-15 as the training set and the data of periods 16-18as the test set. The root mean square error (RMSE), mean absolute error (MAE) and coefficien of determination (R2) were used as the evaluation indexes for the accuracy of the prediction results. The results show that the mean absolute error (MAE) and root mean square error (RMSE)of the PSO-SVR prediction model are smaller compared with the SVR prediction model, and the coefficient of determination reaches 0.9. Comparison and analysis of the two prediction results with the SBAS-InSAR results show that the PSO-SVR model has a stronger learning ability in solving the more complicated nonlinear problems, and the stability of the prediction results is higher.

(3)  Aiming at the special characteristics of the surface rock movement law of coal seam mining in the working face of Muncun mine, according to the geological and mining conditions of Muncun coal mine, a mining subsidence prediction model was established to simulate and analyse the changes of overburden rock and surface rock movement law under different advancing distances of the working face and analyse them by combining with the theory of deformation and numerical simulation experiments. The study shows that: with the advancement of the working face, the scope of the mining hollow area gradually increases, and when the influence of the mining hollow area on the ground surface increases to a certain degree, the ground surface will be subsided and deformed. The maximum subsidence point of the ground surface is in the central position above the mining area, and the subsidence curve is symmetrical about the maximumsubsidence point in the central part of the mining area, and the farther away from the central part of the mining area, the less obvious the ground surface subsidence is under different advancing lengths. However, the symmetry characteristics shown by the immediate working face mining and the single working face mining subsidence in the near horizontal coal seam are differen under the influence of the old mining airspace, the surface subsidence is asymmetrically distributed about the centre of the mining airspace, and the amount of subsidence deformation and thedegree of deformation intensity on the side close to the old mining airspace are obviously greater than that on the side of the unmined area, and the centre of the subsidence is shifted to the direction of the old mining airspace.

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