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基于移动隧道监测系统的隧道位移计算方法。

Method for Tunnel Displacements Calculation Based on Mobile Tunnel Monitoring System.

机构信息

Beijing Advanced Innovation Center for Imaging Theory and Technology, Key Laboratory of 3D Information Acquisition and Application, Ministry of Education, College of Resource Environment and Tourism, Academy for Multidisciplinary Studies, Capital Normal University, Beijing 100048, China.

出版信息

Sensors (Basel). 2021 Jun 27;21(13):4407. doi: 10.3390/s21134407.

DOI:10.3390/s21134407
PMID:34199103
原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC8272133/
Abstract

Efficient, high-precision, and automatic measurement of tunnel structural changes is the key to ensuring the safe operation of subways. Conventional manual, static, and discrete measurements cannot meet the requirements of rapid and full-section detection in subway construction and operation. Mobile laser scanning technology is the primary method for tunnel detection. Herein, we propose a method to calculate shield tunnel displacements of a full cross-section tunnel. The point cloud data, obtained via a mobile tunnel deformation detection system, were fitted, projected, and interpolated to generate an orthophoto image. Combined with the cumulative characteristics of the tunnel gray gradient, the longitudinal ring seam of the tunnel was identified, while the Canny algorithm and Hough line detection algorithm identified the transverse seam. The symmetrical vertical foot method and cross-section superposition analysis were used to calculate the circumferential and radial displacements, respectively. The proposed displacement calculation method achieves automatic recognition of a ring seam, reduces human-computer interaction, and is fast, intelligent, and accurate. Furthermore, the description of the tunnel deformation location and deformation amount is more quantitative and specific. These results confirm the significance of shield tunnel displacement monitoring based on mobile monitoring systems in tunnel disease monitoring.

摘要

高效、高精度、自动化测量隧道结构变化是保障地铁安全运行的关键。传统的人工、静态、离散测量方法无法满足地铁施工和运营中快速、全断面检测的要求。移动激光扫描技术是隧道检测的主要方法。本文提出了一种计算全断面隧道盾构隧道位移的方法。利用移动隧道变形检测系统获取的点云数据进行拟合、投影和插值，生成正射影像图。结合隧道灰度梯度的累积特征，识别隧道的纵向环缝，利用 Canny 算法和 Hough 线检测算法识别横向环缝。采用对称垂直脚法和截面叠加分析分别计算环向和径向位移。所提出的位移计算方法实现了环缝的自动识别，减少了人机交互，具有快速、智能、准确的特点。此外，对隧道变形位置和变形量的描述更加定量和具体。这些结果证实了基于移动监测系统的盾构隧道位移监测在隧道病害监测中的重要意义。

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2
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3
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4
Deformation Monitoring of Metro Tunnel with a New Ultrasonic-Based System.基于新型超声波系统的地铁隧道变形监测
Sensors (Basel). 2017 Aug 1;17(8):1758. doi: 10.3390/s17081758.
5
Automatic Extraction of Tunnel Lining Cross-Sections from Terrestrial Laser Scanning Point Clouds.从地面激光扫描点云自动提取隧道衬砌横截面
Sensors (Basel). 2016 Oct 6;16(10):1648. doi: 10.3390/s16101648.
6
Automated As-Built Model Generation of Subway Tunnels from Mobile LiDAR Data.基于移动激光雷达数据的地铁隧道竣工模型自动生成
Sensors (Basel). 2016 Sep 13;16(9):1486. doi: 10.3390/s16091486.