无人机遥感技术在采煤地面塌陷监测中的应用

发布时间：2018-07-02 13:18

本文选题：无人机遥感技术 + 地面塌陷　；参考：《煤田地质与勘探》2017年06期

【摘要】：为研究无人机遥感技术在采煤地面塌陷监测中的应用,以宁东煤炭基地金凤煤矿011805综采工作面为例,探讨了利用无人机遥感技术进行地表裂缝解译、地面沉降量计算和地面塌陷规律研究的方法。结果表明:无人机飞行航高可根据需要识别的地表裂缝宽度确定,地形平坦地区识别2 cm地表裂缝的飞行航高一般应不超过143 m;地表裂缝宜于采用基于光谱、延长度和紧密度规则的面向对象的信息提取方法进行自动识别,在采用这种方法发现地表塌陷裂缝时宜采用基于边缘检测的图像分割模型和基于Full Lambda Schedule的图像融合模型;对无人机遥感地表高程值进行拟合校正可近似获得采煤工作面地表下沉量和下沉系数,说明无人机遥感技术可应用于采煤地面沉降量监测;综采工作面内地表裂缝数量多,总体垂直回采方向排列,切眼和顺槽附近地表裂缝数量少,总体平行顺槽和切眼展布。
[Abstract]:In order to study the application of UAV remote sensing technology in the monitoring of coal mining ground collapse, taking 011805 fully mechanized mining face of Jinfeng Coal Mine, Ningdong Coal Base, as an example, this paper discusses the interpretation of surface cracks by using UAV remote sensing technology. The method of calculating the amount of land subsidence and studying the law of ground subsidence. The results show that the flight height of UAV can be determined according to the width of surface cracks that need to be identified, and the flight height of identifying 2 cm surface cracks in flat terrain areas should generally not exceed 143 m.The surface cracks are suitable to be based on spectrum. The object oriented information extraction method based on extension and tightness rules is used to identify the surface collapse cracks automatically. The image segmentation model based on edge detection and the image fusion model based on full Lambda schedule are adopted in this paper. The surface subsidence and subsidence coefficient of coal mining face can be approximately obtained by fitting and correcting the remote sensing surface elevation value of UAV, which indicates that UAV remote sensing technology can be used to monitor the surface subsidence of coal mining, and there are many cracks in the interior of fully mechanized coal mining face. The total vertical mining direction is arranged, the number of surface cracks near the cut and the shun groove is less, and the overall parallel trench and the cut hole are distributed.
【作者单位】：西安科技大学地质与环境学院;宁波宁大地基处理技术有限公司;中国地质调查局西安地质调查中心;
【基金】：国家自然科学基金项目(41472234) 中国地质调查局项目(121201011000150022)~~
【分类号】：TD325.4

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