综合GPS技术与灰色模型的西郝庄铁矿开采沉陷预计

Prediction of the Mining Subsidence of Xihaozhuang Iron Mine Based on GPS Technique and Grey Model

矿区开采产生的空区易引发地表沉陷、塌陷等一系列地质灾害问题,严重威胁矿区及周边生态环境。以西郝庄铁矿为例,在分析矿区地质特征的基础上,基于GPS监测技术原理,构建了西郝庄铁矿地表沉陷监测网;然后采用该GPS沉陷监测网获取的监测数据,基于灰色理论构建了G（1,1）沉陷预计模型,给出了监测点的沉陷预计公式;最后通过Matlab软件构建了矿区数字高程模型,并对矿区地表沉陷较严重的部位进行了预计。研究表明：1矿区大部分区域的累计沉陷值基本小于40 mm,发生地面塌陷的可能性较小,CD3-#、CD4-#、CD5-#、CD6-#点附近沉陷值较大,约60 mm;2G（1,1）模型的预计值与实测值的误差分别为1.38%（CD3-#点）、0.56%（CD9#点）,预计值和实测值构建的矿区数字高程模型基本一致,表明G（1,1）模型对于矿区开采沉陷的预计有一定的精度。

The gob caused by mining production can result in the surface mining subsidence,collapse and other geological hazards,which is a serious threat to the ecological environment of the mining area and its surrounding area. Taking the Xihaozhuang iron mine as the study background,firstly,based on analyzing the monitoring principle of the GPS monitoring technique,the surface mining subsidence monitoring GPS network is established; then,based on the monitoring data of the mining subsidence GPS network,the G（ 1,1） grey prediction model is constructed,and the mining subsidence prediction formulas of the GPS monitoring points are given; the digital evaluation model of the mining area are established respectively based on the prediction data and monitoring data,besides that,the mining subsidence serious regions of the mining area are predicted effectively. The study results show that： 1the accumulated mining subsidence value of the mining area are lower than 40 mm,the possibility of surface collapse is small in the mining area,the mining value of the surrounding areas of the CD3-#、CD4-#、CD5-#、CD6-#points are higher than others,about 30 mm; 2the error between the prediction values obtained by the newly established G（ 1,1） prediction model and the monitoring data in the mining area are 1. 38%（ CD3-#） 、0. 56%（ CD9-#）,the digital evaluation model（ DEM） established by the mining subsidence value is consistent to the one established by the actual monitoring value in the mining area,which indicated that the G（ 1,1） prediction model is suitable to predict the mining subsidence in the mining area,and the prediction accuracy is ideal.