油气管沟土石方开挖量激光点云直接测量法

1.中国石油大学(北京)机械与储运工程学院;2.国家管网集团西气东输分公司;3.新疆工程学院安全科学与工程学院

油气管道;管沟开挖;土石方测量;激光点云;半径滤波法;微元积分法

Direct measurement of earthwork excavation for oil and gas pipeline trenches using laser point cloud method
GENG Huan1,2,ZHAO Guozhong2,GU Jijun1,3,MA Ning1,JI Zhongli1

1.College of Mechanical and Transportation Engineering, China University of Petroleum (Beijing); 2.PipeChina West-East Gas Pipeline Company; 3.School of Safety Science and Engineering, Xinjiang University of Engineering

oil and gas pipeline, pipeline trench excavation, earthwork measurement, laser point cloud, radius filtering, infinitesimal integration

DOI: 10.6047/j.issn.1000-8241.2025.02.009

备注

【目的】管沟土石方测量是油气管道建设工程中关键的一环,测量结果将直接影响资源分配、工程进度管理等,选取一种高效、高精度的土石方测量方法至关重要。【方法】利用激光点云直接测量法对管沟开挖前的原始底层、开挖后的管沟区域进行机载雷达扫描,提取地基与管沟两组点云数据,通过半径滤波法进行高空噪点过滤。对点云数据提纯后,根据施工桩号确定管道中心线,沿管道中心线对点云进行横切片划分;再对每段横切片进行竖直切片划分,基于竖直切片下表层层高遍历两组点云数据,完成管沟轮廓点云提取。将区域切分结果作为体积微元,分别计算直段与弧段的微元体积并进行累加,即可完成土石方体积微元积分法求解。【结果】将该测量方法应用于陕甘宁地区某管道的13个试验区域:在区域1~区域5,完成算法参数测试,得出横切片厚度、竖直切片厚度、竖直切片下表层层高的最优参数解分别为0.20m、0.10m、0.05m;在区域6、区域7,完成算法重复性测试,总平均误差为4.72%,具有良好的测量效果;在区域8~区域13,将新方法与大疆智图、GlobalMapperPro、倾斜摄影等方法进行对比测试,结果显示,激光点云直接测量法精度高,平均误差仅为5.84%。【结论】采用激光雷达采集点云具有更高的测量精度、更广泛的工况适用性,且利用直接法规避了间接法的建模精度损失;采集原始地貌作为基准面,降低了常用直接法将坑口平面作为基底产生的误差。(图8表5,参[24]
[Objective] Pipeline trench earthwork measurement is a critical component of oil and gas pipeline construction, as its results directly influence resource allocation and progress management. Therefore, selecting an efficient and accurate measuring method is essential. [Methods] Using the laser point cloud direct measurement method, both the primary substratum before pipeline trench excavation and the excavated trench area were scanned with airborne radar to obtain two point cloud datasets: one for the foundation and one for the pipeline trench. High-altitude noise was then filtered using the radius filtering method. After refinement of the point cloud data, the point cloud was sliced transversely along the pipe centerline based on construction chainage, followed by vertical slicing of each transverse slice. Two point cloud datasets were then traversed according to the height of the lower surface layer in the vertical slices, allowing for the extraction of the pipeline trench profile point cloud. The slicing results were treated as infinitesimal volume elements, with the infinitesimal volumes of both straight and arc sections calculated and aggregated to determine the earth-rock volume using the infinitesimal integration method. [Results] The method was implemented in 13 testing areas along a pipeline in the Shaanxi–Gansu–Ningxia region, with algorithm parameters tested in areas 1–5. The optimal parameters determined were a transverse slice thickness of 0.20 m, a vertical slice thickness of 0.10 m, and a lower surface layer height of 0.05 m for vertical slices. The algorithm’s repeatability was tested in areas 6–7, yielding a total average error of 4.72% and demonstrating effective measurement performance. Comparison tests conducted in areas 8–13 with DJI, Global Mapper Pro, and oblique photography demonstrated that the laser point cloud method achieved a high measurement accuracy, with an average error of only 5.84%. [Conclusion] Utilizing LiDAR for point cloud collection offers higher measurement accuracy and broader applicability across varying conditions. The direct method eliminates the modeling accuracy loss associated with indirect methods, and using the primary landform as the datum plane reduces errors typically introduced by using the pithead plane as the base in conventional direct methods. (8 Figures, 5 Tables, 24 References)
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