基于点云数据的轨道结构与隧道空间限界一体化自动检测方法研究

为了保证列车运营安全,需要在日常运营过程中进行隧道限界检测,但现有检测方法存在测量干扰大、效率低、断面非连续性、与轨道结构相互独立等不足。为此,提出一种基于点云数据的轨道结构与隧道空间限界一体化自动检测方法。在通过中轴线拟合提取隧道任意位置断面的基础上,建立基于钢轨顶面的隧道限界检测坐标系,引入不同类型的隧道限界框,采用改进射线算法实现多种隧道类型的限界自动检测分析。对既有铁路隧道进行现场实验表明,采用该方法可实现侵限位置和侵限尺寸值的准确获取,并给出侵限断面图,满足隧道检测精度要求,在隧道日常运营维护中能够发挥重要作用。

Research on the Integrated Automatic Detection Method of Track Structure and Tunnel Space Clearance Based on Point Cloud Data

In order to ensure operational security, it is necessary to conduct tunnel clearance detection in the daily operation process. However, the existing detection methods have some shortcomings, such as large measurement interference, low efficiency, discontinuity of section, and independence of track structure. Therefore, an integrated automatic detection method for track structure and tunnel space clearance is proposed based on point cloud data. On the basis of extracting tunnel section at any position by fitting the central axis, the coordinate system of tunnel clearance detection based on rail top surface is established, and different standard sizes of tunnel clearance are introduced. The improved ray algorithm method is used to realize automatic detection and analysis of various tunnel types. Field test on existing railway tunnels shows that this method can accurately acquire intrusion location and size values, and provide the drawing of intrusion profile, which can meet the requirements of tunnel clearance detection accuracy and play an important role in the daily maintenance of tunnels.