基于无人机载三维激光扫描测量系统的采空区扫描及应用研究

Research on goaf scanning and application based on unmanned aerial vehicle 3D laser scanning

  • 摘要: 针对地下矿山两步骤回采过程中采空区边界影响相邻矿房回采质量,且传统测量手段往往无法获得完整边界数据的现状,文中采用无人机载三维激光扫描测量系统对某地下铁矿山采空区进行了扫描测量,评估其扫描数据的单点误差最大约为3.6 cm,任意两点间距离平均误差约为2.0 cm,说明其扫描精度较高。在此基础上,快速获得相邻一步骤采空区三维模型,并对一步骤采场的贫化和损失指标进行了预测分析,得出由于一步骤矿房超挖造成的实际矿房贫化率增加值为3.46%,因矿柱损失造成的矿房理论损失率为13.11%,为矿山实际开展二步骤矿房回采设计提供了数据支撑,为优化回采设计方案以达到最大的矿房回收效益奠定了基础。

     

    Abstract: The goaf boundary affects the mining quality of adjacent stopes during the two-step mining process in underground mines, but complete boundary data cannot be obtained well by traditional measurement methods. In this paper, the unmanned aerial vehicle 3D laser scanning measurement system was used to scan and measure the goaf in an underground iron mine. The maximum single point error of the scanning data was approximately 3.6 cm, and the distance error between any two points was approximately 2.0 cm, indicating its high scanning accuracy. On the basis of that, the 3D model of the adjacent goaf was soon obtained, and the dilution and loss indexes of the stope in the first step were predicted and analyzed. It was concluded that the increase value of the actual room dilution rate due to overcutting room in the first step was 3.46%, while the rate of theoretical room loss caused by pillar loss was 13.11%. The above results provide data support for the actual two-step stope design and lay a foundation for optimizing the stope design scheme to maximize the recovery benefit of the stope.

     

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