基于机器视觉的地铁隧道结构变形监测方法
柏文锋1罗海涛1雷雨2陈文均2胡彪2刘肖琳2
Subway Tunnel Structural Deformation Monitoring Method Based on Machine Vision Measurement
BAI Wenfeng1LUO Haitao1LEI Yu2CHEN Wenjun2HU Biao2LIU Xiaolin2
-
作者信息:1.广州地铁设计研究院股份有限公司， 510010， 广州
2.深圳大学物理与光电工程学院， 518061， 深圳
-
Affiliation:1.Guangzhou Metro Design and Research Institute Co., Ltd., 510010, Guangzhou, China
2.College of Physics and Optoelectronic Engineering, Shenzhen University, 518061, Shenzhen, China
-
关键词:
-
Key words:
-
DOI:10.16037/j.1007－869x.20230967
-
中图分类号/CLCN:U456
-
栏目/Col:土建工程
摘要:
［目的］隧道变形关系到隧道结构的健康情况，准确监测隧道变形对隧道安全非常重要。传统人工测量方法虽然较为精准，但耗时耗力，难以满足大规模隧道高效运维需求；自动监测手段以进口全自动全站仪为主，测量范围有限、设备成本高，亟需开发高效、低成本的测量新技术。［方法］基于机器视觉测量，在单相机模式下实现地铁隧道结构大范围多点变形监测，可兼顾监测频率和精度，且具有简便快捷的优点。首先，选定相机参数后，对各个监测点位置处的放大倍数进行标定；同时在监测过程中采用灰度质心法快速计算光斑中心坐标及其变化量；最后通过放大倍数实现像素坐标变化量到实际物理坐标的转换，从而得到各个监测点实际的位移变形。［结果及结论］基于机器视觉测量方法，在地铁隧道内，针对120 m长隧道段进行了28 d位移监测试验，试验结果表明待测隧道段水平与竖直位移量均在1.5 mm以内，并且均存在周期性波动的整体趋势。这验证了通过机器视觉监测地铁隧道，可以实现对地铁隧道毫米级变形量的长时间连续准确监测。
Abstracts:
［Objective］ Tunnel deformation is related to the health of the tunnel structure, and accurate monitoring of tunnel deformation is very important for tunnel safety. Although traditional manual measurement methods are relatively accurate, the time-consuming and labor-intensive defects making it difficult to meet the efficient operation and maintenance requirements of large-scale tunnels; while automatic monitoring methods are mainly based on imported fully automatic total stations, with limited measurement range and high equipment costs. It is urgent to develop new efficient and low-cost measurement technologies. ［Method］ Based on machine vision measurement, large-scale multi-point deformation monitoring of subway tunnel structures can be achieved in a single-camera mode, which can take into account both monitoring frequency and accuracy, featuring the advantages of being simple and fast. First, after selecting the camera parameters, the magnification at each monitoring point is calibrated; at the same time, the grayscale centroid method is used to quickly calculate the center coordinates of the light spot and its change during the monitoring process; finally, the magnification is used to realize the conversion of pixel coordinate changes to actual physical coordinates, thereby obtaining the actual displacement deformation of each monitoring point. ［Result & Conclusion］ Based on machine vision methods, a 28-day displacement monitoring experiment is conducted on a 120m subway tunnel section. The experimental results show that both the horizontal and vertical displacements of the target tunnel section are within 1.5mm, and both exhibit an overall trend of periodic fluctuations. This verifies that machine vision monitoring of subway tunnels can achieve long-term continuous and accurate monitoring of millimeter-level subway tunnel deformation.
过刊浏览
资料下载
友情链接