基于三维激光扫描的煤矿巷道形变监测方法

戴文祥, 陈雷, 闫鹏飞, 王利欣, 李波, 袁鹏喆

戴文祥,陈雷,闫鹏飞,等. 基于三维激光扫描的煤矿巷道形变监测方法[J]. 工矿自动化,2023,49(10):61-67, 95. DOI: 10.13272/j.issn.1671-251x.2023010045
引用本文: 戴文祥,陈雷,闫鹏飞,等. 基于三维激光扫描的煤矿巷道形变监测方法[J]. 工矿自动化,2023,49(10):61-67, 95. DOI: 10.13272/j.issn.1671-251x.2023010045
DAI Wenxiang, CHEN Lei, YAN Pengfei, et al. A deformation monitoring method for coal mine roadway based on 3D laser scanning[J]. Journal of Mine Automation,2023,49(10):61-67, 95. DOI: 10.13272/j.issn.1671-251x.2023010045
Citation: DAI Wenxiang, CHEN Lei, YAN Pengfei, et al. A deformation monitoring method for coal mine roadway based on 3D laser scanning[J]. Journal of Mine Automation,2023,49(10):61-67, 95. DOI: 10.13272/j.issn.1671-251x.2023010045

基于三维激光扫描的煤矿巷道形变监测方法

基金项目: 国家自然科学基金项目(52104196)。
详细信息
    作者简介:

    戴文祥(1969—),男,山东济宁人,高级工程师,主要从事煤炭开采方面的工作,E-mail:84206520@qq.com

  • 中图分类号: TD353

A deformation monitoring method for coal mine roadway based on 3D laser scanning

  • 摘要: 针对传统煤矿巷道形变监测方法存在数据采集不全面、数据形式不直观、精度差、不能实现对全巷道形变连续监测等问题,提出了一种基于三维激光扫描的煤矿巷道形变监测方法。首先利用三维激光扫描技术获取煤矿巷道真实的三维点云数据;其次利用深度学习模型VoxelNet对三维激光扫描数据进行检测去噪,将无序的点云数据转换成高维特征数据;再次利用alphashape算法对提取的巷道断面离散点进行拟合,并采用基于差值的方法对数据进行多维差值计算,以得到巷道形变的具体数据,实现矿区巷道形变监测的全覆盖。将三维激光扫描技术应用于塔山煤矿30507工作面的形变监测,对巷道三维点云数据进行了截面分析和三维整体分析。分析结果表明:通过2期巷道截面轮廓的相对偏差,可直接观测该区域的主要形变,如果上轮廓向内偏离则顶板发生塌陷;如果下轮廓向外偏离,则底板发生鼓起。随着测点距工作面的距离越近,附色模型的颜色越偏向红色和蓝色,且颜色越深,巷道形变越大。
    Abstract: The traditional monitoring methods for coal mine roadway deformation have problems such as incomplete data collection, non intuitive data format, poor precision, and inability to achieve continuous monitoring of the entire roadway deformation. In order to solve the above problems, a deformation monitoring method for coal mine roadway based on 3D laser scanning is proposed. Firstly, the method uses 3D laser scanning technology to obtain real 3D point cloud data of coal mine roadways. Secondly, the deep learning model VoxelNet is used to detect and denoise 3D laser scanning data, converting unordered point cloud data into high-dimensional feature data. The Alphashape algorithm is used to fit the discrete points of the extracted roadway cross-section. The multi-dimensional difference calculation based on the difference method is used to obtain specific data of roadway deformation, achieving full coverage of roadway deformation monitoring in the mining area. The 3D laser scanning technology is applied to deformation monitoring of the 30507 working face in Tashan Coal Mine. The cross-sectional analysis and 3D overall analysis are conducted on the 3D point cloud data of the roadway. The analysis results indicate that the main deformation in the area can be directly observed through the relative deviation of the section contour of the second stage roadway. If the upper contour deviates inward, the roof will collapse. If the lower contour deviates outward, the floor will bulge. As the distance between the measuring point and the working face gets closer, the color of the attached color model leans towards red and blue. The darker the color, the greater the deformation of the roadway.
  • 图  1   三维激光点坐标计算原理

    Figure  1.   Principle of 3D laser point coordinate calculation

    图  2   alphashape算法计算圆心原理

    Figure  2.   Diagram of alphashape algorithm calculating the center of a circle

    图  3   控制点坐标录入

    Figure  3.   Control point coordinate input

    图  4   选取的噪点数据

    Figure  4.   Selected noise data

    图  5   去噪后数据

    Figure  5.   Denoised data

    图  6   煤矿巷道点云数据内部视角

    Figure  6.   Internal perspective of point cloud data in coal mine roadway

    图  7   煤矿巷道点云数据外部视角

    Figure  7.   External perspective of point cloud data of coal mine roadway

    图  8   三维整体分析结果

    Figure  8.   3D overall analysis results

    图  9   巷道截面分析结果

    Figure  9.   Roadway section analysis results

    图  10   巷道截面对比

    Figure  10.   Comparison of roadway section

    图  11   巷道形变预警记录

    Figure  11.   Roadway deformation warning record

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出版历程
  • 收稿日期:  2023-01-17
  • 修回日期:  2023-10-16
  • 网络出版日期:  2023-10-22
  • 刊出日期:  2023-10-24

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