基于GB-SAR的矿山边坡局部变形演化与失稳预测

Local deformation evolution and instability prediction of mining slopes based on GB-SAR

为了提高地基合成孔径雷达(ground-based synthetic aperture radar, GB-SAR)边坡监测效果与失稳预测能力,在广东省某石灰石矿山架设地基雷达,开展实地监测试验,结合矿山地质条件与监测数据研究不同类型的岩体变形演化特征,根据变形特征选择位移最大点的监测数据利用速度倒数法进行失稳预测。通过分析典型案例的监测数据来优化速度倒数法的算法,进而对矿山试验数据进行研究。研究结果表明:通过分析雷达三维模型变形图的局部位移差异,能够初步判断边坡岩体的变形破坏方式;适当增大移动平均滤波法的移动时间周期C,能够更早地发现灾害征兆,更好地识别岩体加速变形阶段及临滑阶段。研究结果可为基于雷达的滑坡预测提供参考。

In order to improve the slope monitoring effect and instability prediction ability of ground-based synthetic aperture radar(GB-SAR),a ground-based radar was installed in a limestone mine in Guangdong,and the field monitoring experiments were conducted.Based on the geological conditions and monitoring data of mine,the deformation evolution characteristics of different types of rock masses were studied.According to the deformation characteristics,the monitoring data of the maximum displacement point was selected for instability prediction using the reciprocal velocity method.By analyzing the monitoring data of typical cases,the algorithm of the reciprocal speed method was optimized,and then the experimental data of this mine was studied.The results show that by analyzing the local displacement differences in the deformation map of the radar 3D model,the deformation and failure mode of the slope rock mass can be preliminarily determined.Appropriately increasing the moving time period C of the moving average filtering method can detect the disaster signs earlier and better identify the accelerated deformation stage and critical sliding stage of the rock mass.The research results can provide reference for the landslide prediction based on radar.