张永庭, 徐友宁, 梁伟, 魏采用, 李樵民, 杨雪茹, 拜剑虹. 2018: 基于无人机载LiDAR的采煤沉陷监测技术方法——以宁东煤矿基地马连台煤矿为例. 地质通报, 37(12): 2270-2277.
    引用本文: 张永庭, 徐友宁, 梁伟, 魏采用, 李樵民, 杨雪茹, 拜剑虹. 2018: 基于无人机载LiDAR的采煤沉陷监测技术方法——以宁东煤矿基地马连台煤矿为例. 地质通报, 37(12): 2270-2277.
    ZHANG Yongting, XU Youning, LIANG Wei, WEI Caiyong, LI Qiaomin, YANG Xueru, BAI Jianhong. 2018: Technical methods for colliery subsidence disaster monitoring using UAV LiDAR: A case study of the Maliantai colliery, Ningdong coal base, Ningxia. Geological Bulletin of China, 37(12): 2270-2277.
    Citation: ZHANG Yongting, XU Youning, LIANG Wei, WEI Caiyong, LI Qiaomin, YANG Xueru, BAI Jianhong. 2018: Technical methods for colliery subsidence disaster monitoring using UAV LiDAR: A case study of the Maliantai colliery, Ningdong coal base, Ningxia. Geological Bulletin of China, 37(12): 2270-2277.

    基于无人机载LiDAR的采煤沉陷监测技术方法——以宁东煤矿基地马连台煤矿为例

    Technical methods for colliery subsidence disaster monitoring using UAV LiDAR: A case study of the Maliantai colliery, Ningdong coal base, Ningxia

    • 摘要: 探索采煤地表沉陷的高新监测技术方法是推动采煤沉陷监测的重要工作,无人机载LiDAR采煤塌陷监测技术是无人机与LiDAR构建的一种新型低空三维空间测量技术。以宁东煤炭基地马莲台煤矿采煤沉陷区为例,采用无人机机载LiDAR监测技术获取了2017年4月及8月2期三维点云数据,通过数据三维建模和沉降信息提取,得到了地面沉陷情况的三维立体图,监测出了3处地面沉降区,并利用实测水准点和已有GPS自动监测站数据,对该技术监测地面沉降的精度进行评估。研究结果表明,无人机机载LiDAR监测技术方法可满足采煤塌陷的立体监测需求,具有机动灵活、成本低、效率高、精度高等特点,未来可在类似地区推广应用。

       

      Abstract: Exploring advanced technology of coal-mining subsidence disaster monitoring is an important task to promote the monitoring better. Colliery subsidence disaster monitoring using UAV LiDAR is a new technology of low-flying 3D measurement composed of UAV and LiDAR. In this study, the authors chose the typical subsidence area of Maliantai colliery, Ningdong coal base in Ningxia as the study area, and obtained point cloud data of two time periods in April and August 2017 in the study area based on UAV LiDAR data. The authors obtained the 3D stereogram of colliery subsidence disaster by information extraction and 3D modeling and discovered 3 colliery subsidence disaster areas. Also, using a certain number of existent leveling points and GPS automatic monitoring data, the authors evaluated the accuracy of the model. The results show that the technical methods of colliery subsidence disaster monitoring using UAV LiDAR data meet the requirements of relevant specification. The methods have such features as flexibility, low cost, high efficiency and high precision, and have wide popularization and application value in future.

       

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