基于D-InSAR技术和灰色Verhulst模型的矿区沉降监测与预计  

Monitoring and Prediction of Mining Subsidence based on D-InSAR and Gray Verhulst Model

作　　者：杨俊凯[1,2] 范洪冬[1,2] 赵伟颖[1,2] 冯军[1,2] 

机构地区：[1]国土环境与灾害监测国家测绘地理信息局重点实验室,江苏徐州221116 [2]中国矿业大学环境与测绘学院,江苏徐州221116

出　　处：《金属矿山》2015年第3期143-147,共5页Metal Mine

基　　金：国家自然科学基金项目(编号:41272389);江苏高校优势学科建设工程项目(编号:SZBF2011-6-B35);江苏省基础研究计划(自然科学基金)青年基金项目(编号:BK20130174)

摘　　要：针对在地形复杂的矿区沉降观测资料不易获取的问题,将合成孔径雷达差分干涉技术（D-In SAR）与灰色Verhulst模型相结合,提出了一种矿山开采沉陷监测和预计方法。该方法首先对覆盖大柳塔煤矿某工作面的12景Terra SAR-X雷达数据进行D-In SAR处理,获取观测站沉降值;然后根据沉降量与时间的关系建立了基于灰色Verhulst模型的预测函数,对开采沉陷发展规律进行分析。试验结果表明：3个测试点D-In SAR监测数据的绝对和相对误差分别为2.8~15 mm,0.9%~6%;结合灰色Verhulst模型预测的绝对和相对误差分别为3.4~18.8 mm,1.2%~5.7%。上述研究结果进一步表明,所提出的方法可有效弥补矿区沉降实测数据的不足,为实现矿区开采沉陷监测和预计的一体化软件设计提供参考。It is not easy to obtain the observation data of mining subsidence of the mining area with complex terrain. In order to solve the problem,a new mining subsidence monitoring and prediction method based on the combination of synthetic aperture radar differential interferometry（ D-In SAR） technique and grey Verhulst model is proposed. Firstly,the 12 Terra SARX images that covered the experimental areas in the one working face of Daliuta coal mine are processed by using D-In SAR technique to obtain the subsidence values of observation stations. Secondly,the prediction function of grey Verhulst model is established based on the relationship of subsidence value and time to analyze the development law of mining subsidence. The experimental results show that,the absolute and the relative errors of D-In SAR monitoring values for three points are varied from2. 8 to 15 mm,and 0. 9% to 6% respectively; The absolute error and relative error in prediction based on the grey Verhulst model Combined with D-In SAR technique are varied from 3. 4 to 18. 8 mm,and from 1. 2% to 5. 7% respectively. The experimental results above further indicate that,the method proposed in this paper can effectively make up the inadequacy of the measured data and provide reference for realizing the integration of mining subsidence monitoring and prediction.

关 键 词：沉降监测与预计 D-INSAR 灰色VERHULST模型 预测函数 

分 类 号：TD67[矿业工程—矿山机电]