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GPR Detection of Tunnel Lining Cavities and Reverse-time Migration Imaging

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Abstract

Tunnel lining cavity is one of the diseases that threaten the safe operation of tunnel, so it has been the attention of test personnel. As a nondestructive testing method, Ground Penetrating Radar (GPR) has been widely used in tunnel lining disease inspection. In order to improve the detection accuracy and success rate of tunnel lining cavities, this paper applies the reverse-time migration (RTM) algorithm to image tunnel lining cavities with high accuracy. Firstly, the principle of GPR pre-stack RTM is described in detail, in which the finite difference time domain (FDTD) method is used to calculate the forward and backward electromagnetic fields, and the normalized cross-correlation imaging condition is used to obtain the RTM results. On this basis, the GPR RTM program is compiled and applied to the simulated dataset of a typical lining cavity GPR model. The comparison of RTM and Kirchhoff migration result showed that the diffracted wave in the steel bar and cavities has good convergence, and the profile’s resolution is improved effectively; In contrast to the Kirchhoff migration result, the RTM result can better focus the radar diffraction wave energy of the steel bars and cavities on the real space location generated by them, weaken the shielding effect of the steel mesh, and suppress multiple interference and clutter scattering waves. Finally, a physical model of lining cavities was detected by GPR, and the RTM algorithm was applied to data processing and interpretation. The RTM delimits the positions of steel mesh and cavities effectively, and the interpretation accuracy of GPR profile has been improved, which provide a scientific and effective way for accurately delimit the scope of tunnel lining cavities.

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Authors and Affiliations

  1. College of Earth Sciences, Guilin University of Technology, Guilin, 541004, China

    Yu-zeng Lyu, Hong-hua Wang & Jun-bo Gong

  2. Guangxi Key Laboratory of Hidden Metallic Ore Deposits Exploration, Guilin, 541004, China

    Yu-zeng Lyu & Hong-hua Wang

Authors
  1. Yu-zeng Lyu
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  2. Hong-hua Wang
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  3. Jun-bo Gong
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Corresponding author

Correspondence to Hong-hua Wang.

Additional information

The research work was supported by the National Natural Science Foundation of China (Nos. 41764005, 41604039, 41604102 and 41574078), Guangxi Natural Science Foundation of China (Nos. 2016GXNSFBA380082 and 2016GXNSFBA380215), Guangxi Young and Middle-aged’ Basic Ability Improvement Project (No. KY2016YB199), Guangxi Collaborative Innovation Center for Exploration of Hidden Nonferrous Metal Deposits and Development of New Materials Project (No. GXYSXTZX2017-II-5) and Guangxi Scholarship Fund of Guangxi Education Department.

Lyu Yuzeng graduated with a PhD from the Institute of Applied Geophysics, Central South University, in 2008. He is now an associated professor at the College of Earth Sciences, Guilin University of Technology. His research interest is electromagnetic numerical simulation and inversion imaging. Email: Lyz@glut.edu.cn

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Lyu, Yz., Wang, Hh. & Gong, Jb. GPR Detection of Tunnel Lining Cavities and Reverse-time Migration Imaging. Appl. Geophys. (2020). https://doi.org/10.1007/s11770-019-0831-9

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  • DOI: https://doi.org/10.1007/s11770-019-0831-9

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