基于激光雷达的井下巷道形变量监测算法
Underground roadway shape variable monitoring algorithm based on laser radar
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摘要: 为解决井下巷道形变量的正确监测问题，基于井下智慧车安装高精度激光雷达、车辆辅助定位系统，设计了1种基于激光雷达的井下巷道形变量监测算法；建立了监测算法的总体架构，详细描述了激光雷达数据获取与预处理中的关键技术；基于井下巷道场景监测现有知识积累，围绕离散点特征提取，构建了1种改进型特种点配准算法，解决了巷道场景特征点稀疏、无法有效配准难题；利用点到面的距离挑出离群点，快速计算点的偏移量，并通过DBSCAN的密度聚类算法快速提取大密度离群点，快速筛选变形区域，分析形变程度，实现了井下巷道表面的智能化形变监测。试验结果表明：采用基于激光雷达巷道形变监测算法可以实时动态精准地监测井下巷道表面形态变化，能够保障井下巷道正常运行及保护矿工生命财产安全。Abstract: In order to solve the problem of correct monitoring of underground roadway shape variables, a monitoring algorithm of underground roadway shape variables based on laser radar is designed based on the installation of high-precision laser radar and vehicle aided positioning system in underground intelligent vehicle; the overall framework of the monitoring algorithm is established, and the key technologies in laser radar data acquisition and preprocessing are described in detail; based on the existing knowledge accumulation of underground roadway scene monitoring and around the feature extraction of discrete points, an improved special point registration algorithm is constructed, which solves the problem that the feature points of roadway scene are sparse and can not be registered effectively; the distance from point to surface is used to pick out outliers, quickly calculate the offset of points, quickly extract high-density outliers through the density clustering algorithm of DBSCAN, quickly screen the deformation area, analyze the deformation degree, and realize the intelligent deformation monitoring of underground roadway surface. The test results show that the roadway deformation monitoring algorithm based on laser radar can monitor the roadway surface shape changes under logging in real time, dynamically and accurately, and can ensure the normal operation of underground roadway and protect the safety of miners’ life and property.
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Keywords:
- laser radar /
- deformation monitoring /
- density clustering /
- ICP algorithm /
- underground roadway
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