基于无人机全流程自动建模的露天矿边坡参数校核方法

    Slope parameters check method for open-pit mine based on automatic modeling of UAV whole process

    • 摘要: 露天矿边坡稳定性对矿山安全至关重要,边坡参数的精准识别是保障矿山安全的核心环节,传统边坡参数获取方式存在效率低、数据单一、难以实现全域高频次覆盖等局限性。针对上述问题,提出了一种基于无人机(Unmanned Aerial Vehicle, UAV)全流程自动建模的露天矿边坡参数校核方法,通过智能感知、自动化建模、模型分析技术突破,实现了矿山边坡关键参数的无人化、全域化监测。以内蒙古某大型露天矿为研究对象,基于无人机智能机库技术优化了无人机自动航线规划方法,介绍了机载激光雷达自主作业流程,研究了基于内网穿透的批量数据高效回传机制,提出了适用于露天矿的点云数据自动解算流程,设计了点云局部更新策略以减少数据处理量,基于点云数据建立了露天矿数字表面模型(Digital Surface Model,DSM),通过平盘与坡面提取、骨架线提取实现了平盘宽度、台阶高度、边坡角度等关键参数的全域分析。结果表明:该方法实现了基于无人机机库的点云数据全流程自动建模,自动化程度100%;边坡参数提取精度相较于常规人工测量方式显著提升,平盘宽度、台阶高度误差小于0.5 m,边坡角度误差小于0.5°。通过无人机单次作业即可实现全矿边坡高密度采集与分析,有效提升了露天矿边坡监测的精度与效率,大幅降低了人工巡查成本,为矿山安全生产管理及监管部门核查提供了可靠的数据支持。

       

      Abstract: Slope stability of open-pit mine is very important to mine safety. Accurate identification of slope parameters is the core link to ensure mine safety. Traditional slope parameter acquisition methods have limitations such as low efficiency, single data, and difficulty in achieving high-frequency coverage of the whole region. In view of the above problems, a method for checking the slope parameters of open-pit mine based on the full process automatic modeling of unmanned aerial vehicle (UAV) is proposed. Through the breakthrough of intelligent perception, automatic modeling and model analysis technology, the unmanned and global monitoring of the key parameters of mine slope is realized. Taking the large open-pit mine in Inner Mongolia as the research object, based on the UAV intelligent hangar technology, the automatic route planning method of UAV is optimized. The autonomous operation process of airborne lidar is introduced. The efficient return mechanism of batch data based on internal network penetration is studied. The automatic solution process of point cloud data suitable for open-pit mine is proposed. The local update strategy of point cloud is designed to reduce the amount of data processing. Based on the point cloud data, the digital surface model (DSM) of open-pit mine is established. Through the extraction of flat plate and slope surface and skeleton line, the global analysis of key parameters such as flat plate width, step height and slope angle is realized. The research result shows that this method realizes the automatic modeling of the whole process of point cloud data based on UAV hangar, and the degree of automation is 100%. The accuracy of slope parameter extraction is significantly improved compared with that of conventional mine manual measurement. The error of flat plate width and step height is less than 0.5 m, and the error of slope angle is less than 0.5°. The high-density collection and analysis of the whole mine slope can be realized by a single operation of the UAV, which effectively improves the accuracy and efficiency of the open-pit mine slope monitoring, greatly reduces the cost of manual inspection, and provides reliable data support for mine safety production management and supervision department verification.

       

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