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1.武汉大学遥感信息工程学院,湖北 武汉,430079
2.湖北珞珈实验室,湖北 武汉,430079
3.时空数据智能获取技术与应用教育部工程研究中心,湖北 武汉,430079
4.武汉汉宁轨道交通技术有限公司,湖北 武汉,430010
5.广西交通设计集团有限公司,广西 南宁,530029
Received:19 September 2023,
Published:05 March 2025
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毛庆洲,徐浩轩,朱璟,等.利用高密度点云现场检测在建隧道超欠挖[J].武汉大学学报(信息科学版),2025,50(3):562-570.
MAO Qingzhou,XU Haoxuan,ZHU Jing,et al.Immediate Detection of Over-Under Break of Tunnel Under Construction Using High-Density Point Cloud[J].Geomatics and Information Science of Wuhan University,2025,50(3):562-570.
毛庆洲,徐浩轩,朱璟,等.利用高密度点云现场检测在建隧道超欠挖[J].武汉大学学报(信息科学版),2025,50(3):562-570. DOI:10.13203/j.whugis20220601
MAO Qingzhou,XU Haoxuan,ZHU Jing,et al.Immediate Detection of Over-Under Break of Tunnel Under Construction Using High-Density Point Cloud[J].Geomatics and Information Science of Wuhan University,2025,50(3):562-570. DOI:10.13203/j.whugis20220601
使用高密度三维激光扫描点云进行隧道超欠挖检测,数据量大,计算效率低;要实现即时快速地在线解算,提高检测效率,需要解决隧道中线快速提取、点云下采样和超欠挖快速计算等问题。提出了一种在设计文件监督下的隧道平面外包矩形中线提取算法,能够快速有效构建隧道中线;探究了下采样参数设置的最优方式,提高断面提取和超欠挖计算效率;提出了基于内轮廓的反距离加权超欠挖检测方法,提高超欠挖检测的精度和鲁棒性。实验结果表明,所提的超欠挖检测方式能够实现在线解算、报表生成、模型构建,总长度为40 m的三站测量数据配准拼接
计算耗时247.14 s,超欠挖计算结果与全站仪实测值的相对中误差为0.96 mm,在满足即时快速检测的同时兼顾了高精度。
Objectives
2
High density 3D laser scanning point cloud contains massive data
leading to low efficiency in detection of tunnel over-under break. In order to get the results while measuring
it is necessary to solve problems including fast extraction of tunnel centerline
point cloud data down-sampling and efficient over-under break calculation.
Methods
2
First
we propose a centerline extraction algorithm based on the outer rectangle of tunnel plane and the design file
which can construct the centerline quickly and effectively. Then
we explore the efficiency improvement of section extraction and over-under break calculation by setting the optimal down-sampling parameter. Finally
we propose an over-under break calculation algorithm based on inner contour using inverse distance weighted method.
Results
2
Experiment shows that the proposed algorithm can realize online calculation
generate reports and construct 3D over-under break model. It takes 247.14 s to get over-under break calculation results using the georeferenced point cloud data of 3 measurement stations. Compared with the measured values by total station
the mean square error of the over-under break results of a 40 m section is only 0.96 mm.
Conclusions
2
The proposed algorithm can detect the over-under break in tunnel constructing and meet the requirements of high-precision and immediateness
which could be used during construction of the tunnel project.
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