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Real-Time Tunnel Deformation Monitoring Technology Based on Laser and Machine Vision

Authors :
Hu Wenchuan
Zurong Qiu
Qianhui Sun
Liu Jiachen
Wang Chenglin
Li Haopeng
Source :
Applied Sciences, Volume 8, Issue 12, Applied Sciences, Vol 8, Iss 12, p 2579 (2018)
Publication Year :
2018
Publisher :
Multidisciplinary Digital Publishing Institute, 2018.

Abstract

Structural health monitoring is a topic of great concern in the world, and tunnel deformation monitoring is one of the important tasks. With the rapid developments in tunnel traffic infrastructure construction, engineers need a portable and real-time system to obtain the tunnel deformation during construction. This paper reports a novel method based on laser and machine vision to automatically measure tunnel deformation of multiple interest points in real time and effectively compensate for the environment vibration, and moreover it can overcome the influence of a dusty and dark tunnel environment in low visibility. An automatic and wireless real-time tunnel deformation monitoring system, which is based on laser and machine vision and can give early warnings for tunnel collapse accidents, is proposed. The proposed system uses a fixed laser beam as a monitoring reference. The image acquisition modules mounted on the measured points receive the laser spots and measure the tunnel accumulative deformation and instantaneous deformation velocity. Compensation methods are proposed to reduce measurement errors caused by laser beam feasibility, temperature, air refraction index, and wireless antenna attitude. The feasibility of the system is verified through tunnel tests. The accuracy of the detection system is better than 0.12 mm, the repeatability is less than 0.11 mm, and the minimum resolution is 10 &mu<br />m<br />therefore, the proposed system is very suitable for real-time and automatic detection of tunnel deformation in low visibility during construction.

Details

Language :
English
ISSN :
20763417
Database :
OpenAIRE
Journal :
Applied Sciences
Accession number :
edsair.doi.dedup.....1c167dd7d475b0a8b3c785c65dbbb3d7
Full Text :
https://doi.org/10.3390/app8122579