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Sensors 2017, 17(8), 1758;

Deformation Monitoring of Metro Tunnel with a New Ultrasonic-Based System

School of Civil Engineering and Mechanics, Huazhong University of Science and Technology, 1037 Luoyu Rd., Wuhan 430074, China
School of Earth Sciences and Engineering, Nanjing University, Nanjing 210023, China
Authors to whom correspondence should be addressed.
Received: 15 June 2017 / Revised: 19 July 2017 / Accepted: 22 July 2017 / Published: 1 August 2017
(This article belongs to the Special Issue Sensors for Deformation Monitoring of Large Civil Infrastructures)
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With the rapid construction of metro tunnels in many metropolises, a fast and convenient solution to capture tunnel deformation is desired by civil engineers. This contribution reports an automatic and wireless tunnel deformation monitoring system using ultrasonic transducers. A processing algorithm of the redundant ultrasonic information (RUI) approach is proposed to improve measurement accuracy. The feasibility of this tunnel deformation monitoring method is carefully examined with various probe angles, distances, and surrounding temperature variations. The results indicate that high accuracy can be achieved with different coefficients for various probe angles and sensor distances, as well as temperatures. In addition, a physical tunnel model was fabricated to verify the new processing algorithm of the RUI approach for a wireless tunnel deformation sensing system. The test results reveal that average measurement errors decreased from 7% to 3.75% using the RUI approach. Therefore, it can be concluded that the proposed approach is well suited to the automatic detection of critical conditions such as large deformation events in metro tunnels. View Full-Text
Keywords: tunnel deformation measurement; ultrasonic; wireless; redundant ultrasonic information tunnel deformation measurement; ultrasonic; wireless; redundant ultrasonic information

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Xu, D.-S.; Zhao, Y.-M.; Liu, H.-B.; Zhu, H.-H. Deformation Monitoring of Metro Tunnel with a New Ultrasonic-Based System. Sensors 2017, 17, 1758.

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