The Real-Time Strain Monitoring of Tunnel Supporting Structure and Nonlinear Regression Analysis

Abstract:

Concrete embedded fiber Bragg grating strain sensors are used to monitor real-time strain of each section in the tunnel surrounding rock supporting structure, and the nonlinear regression analysis method is adopted to analysis the real-time measurement data. By using nonlinear regression analysis method, the strain development status of surrounding rock supporting structure can be grasped timely and the variation trend of the strain value of monitoring point can be predicted, which can provides foundations for judging the stability of tunnel supporting structure.

• Periodical: Advanced Materials Research (Volumes 718-720)
• Pages: 837-841
• DOI: https://doi.org/10.4028/www.scientific.net/AMR.718-720.837
• Online since: July 2013
• Authors: Bi He, Bin Wang, Chuan Li, Tong Yao Yang, Zhou Chun Cai, Feng Xiao
• Keywords: Health Monitoring, Nonlinear Regression Analysis, Strain Detection, Tunnel Supporting Structure

References

[1] Shengrui Su, Hehua Zhu, Guofeng Li, Treatment of liner diseases for joint arch tunnel, Chinese Journal of Rock Mechanics and Engineering. 2003, 22(z1): 2510-2515.

[2] Hong Xu, Research on crack propagation regularity and its temperature effect in lining of urban tunnel on service, Journal of Highway and Transportation Research and Development. 2009, 26(10): 93-99.

[3] Hongnan Li, Dongwei Gao, Tinghua Yi, Advances in structural health monitoring systems in civil engineering, Advances in Mechanics. 2008, 38(2): 151-166.

[4] Baihua Long, Xing Hu, Dayong Huang, Xinjie Wang, Nonlinear regression analyze the strain of the enclosing rock of tunnel, Earth and Environment. 2005, 33(z1): 70-73.

[5] Xiumei Wang, Zhuoqiao Zeng, Displacement monitoring during construction and operation for underground projects, China's Manganese Industry. 2001, 19(4): 20-23.

[6] Zhanchang Zhao, Yongli Xie, Xiaohua Yang, Youyun Li, Observation research on the mechanical characteristic of highway tunnel lining in loess, China Journal of Highway and Transport. 2004, 17(1): 66-69.

[7] Zhao X. G, Qiu H. T, Li C, Liu J. P, FBG-based health monitoring for the secondary lining of Bainijing tunnel No.3 in Kunming, China, Proceedings and Monographs in Engineering, Water and Earth Sciences. 2008: 781-786.

DOI: 10.1201/9780203883204.ch146

[8] Chuan Li, Yonggui Zhao, Hao Liu, Zhou Wan, Chen Zhang, Ning Rong, Monitoring second lining of tunnel with mounted fiber Bragg grating strain sensors, Automation in Construction. 2008, 17(5): 641-644.

DOI: 10.1016/j.autcon.2007.11.001

[9] Chuan Li, Yonggui Zhao, Hao Liu, Zhiling Zhang, Zhou Wan, Dan Li, Yurui Hu, Jing You, Combined Interrogation using an Encapsulated FBG Sensor and a Distributed Brillouin Tight Buffered Fiber in Tunnel, Structural Health Monitoring. 2010, 9(4): 341-346.

DOI: 10.1177/1475921710361321

[10] Jianguo Xu, Fuming Wang, Yingchun Cai, Convergence deformation monitoring of tunnel and characteristic parameter back analysis of surrounding rock, China Journal of Highway and Transport. 2008, 21(3): 81-85.

[11] Zhang Q, Qu C. Y, Kang Y. L, Huang G. Y, Cai Z. X, Zhao Y, Zhao H. F, Su P. C, Identification and optimization of energy consumption by shield tunnel machines using a combined mechanical and regression analysis, Tunnelling and Underground Space Technology. 2012(28): 350-354.

DOI: 10.1016/j.tust.2011.12.003

[12] Dingli Zhang, Jun Huang, analysis and prediction of vault crown settlement in metro tunneling at shallow depth, Chinese Journal of Rock Mechanics and Engineering. 2005, 24(10): 1703-1709.