煤矿井下巷道点云变形检测及可视化研究  

Research on Point Cloud Deformation Detection and Visualization in Underground Coal Mine Tunnels

作　　者：穆莉莉[1] 杨紫威 刘帅帅 王天棋 李训杰 Mu Lili;Yang Ziwei;Liu Shuaishuai;Wang Tianqi;Li Xunjie(School of Mechanical and Electrical Engineering,Anhui University of Science and Technology,Huainan,Anhui 232001,China)

机构地区：[1]安徽理工大学机电工程学院,安徽淮南232001

出　　处：《黑龙江工业学院学报（综合版）》2024年第7期105-112,共8页Journal of Heilongjiang University of Technology(Comprehensive Edition)

基　　金：安徽省重点研究与开发计划项目“基于三维激光线扫描技术的煤矿巷道形变视觉监测关键技术研究”(项目编号:202004a07020046)。

摘　　要：为解决煤矿井下巷道变形传统检测的非连续、效率低、智能化程度低的问题,提出一种深度相机与激光雷达点云融合三维空间重构后进行变形分析的新方法。设计了点云切片及提取骨骼线算法,建立了巷道变形检测模型。三维点云处理复杂,算法集成难度大,基于Qt开发了可视化变形监控软件,通过信号槽机制完成人机交互设计。测试表明,系统可对巷道全域进行自动连续检测,变形检测精度高,软件具有良好的人机交互性。In order to solve the problems of discontinuity,low efficiency,and low intelligence level in traditional deformation detection of underground coal mine tunnels,a new method of analyzing deformations by fusing depth cameras and LIDAR point clouds for three-dimensional space reconstruction is proposed.An algorithm for point cloud slicing and skeleton line extraction is designed,and a tunnel deformation detection model is established.Due to the complexity of processing three-dimensional point clouds and the difficulty of integrating algorithms,a visualization deformation monitoring software is developed based on Qt,which achieves human-machine interaction design through signal-slot mechanism.Tests show that the system can automatically and continuously detect the whole region of the tunnel,with high deformation detection accuracy and good human-machine interaction of the software.

关 键 词：巷道变形检测 骨骼线提取 点云切片 QT 可视化 

分 类 号：TD679[矿业工程—矿山机电] TP311[自动化与计算机技术—计算机软件与理论]