Volume 23 Issue 4
Aug.  2023
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GENG Qing-qiao, JIA Yuan-hua, YE Ying, WANG Deng-ke. Improved transient electromagnetic radar method of void identification behind tunnel lining[J]. Journal of Traffic and Transportation Engineering, 2023, 23(4): 218-232. doi: 10.19818/j.cnki.1671-1637.2023.04.016
Citation: GENG Qing-qiao, JIA Yuan-hua, YE Ying, WANG Deng-ke. Improved transient electromagnetic radar method of void identification behind tunnel lining[J]. Journal of Traffic and Transportation Engineering, 2023, 23(4): 218-232. doi: 10.19818/j.cnki.1671-1637.2023.04.016
shu

Improved transient electromagnetic radar method of void identification behind tunnel lining

doi: 10.19818/j.cnki.1671-1637.2023.04.016
  • 1.

    School of Traffic and Transportation, Beijing Jiaotong University, Beijing 100044, China

  • 2.

    Beijing Key Laboratory of Underground Engineering Construction Prediction and Precaution, Beijing Municipal Engineering Research Institute, Beijing 100037, China

  • 3.

    School of Civil Engineering, Beijing Jiaotong University, Beijing 100044, China

Funds:

National Natural Science Foundation of China 52178379

Fundamental Research Funds for the Central Universities 2021YJS080

More Information
  • Author Bio:

    GENG Qing-qiao(1994-), male, doctoral student, 20114066@bjtu.edu.cn

    JIA Yuan-hua(1962-), male, professor, PhD, yhjia@bjtu.edu.cn

  • Received Date: 2023-02-13
  • Publish Date: 2023-08-25
    Abstract
  • In view of the technical problems of detection behind the tunnel lining such as insignificant image features, and the low accuracies of void location and range identification, an improved transient electromagnetic radar (TER) method to detect the void behind the lining was proposed based on the transient electromagnetic theory and the detection requirements of tunnel lining structure. The detection depth was increased by improving the turn-off time of the transmitting system. The image resolution was improved by using the equivalent circuit of receiving coil and weak signal enhancement algorithm. On the basis of eliminating the strong interference signal and increasing the transmitting magnetic moment, the data noise was suppressed by smooth filtering and multi-period superimposed sampling. Based on the difference in the apparent resistivity, the TER map of the relevant medium of lining structure was established, and the indoor lining defect simulation test was carried out through the different combinations of various concrete components. The detection accuracy and feasibility of the improved TER method to detect the void behind the lining were preliminarily evaluated. A field application was carried out in Haobei Tunnel of Beijing Metro Line 6. By comparing the test results of TER images with the sampling results of drilling, the effectiveness of the improved TER method to detect the void behind the lining was further verified. Analysis results show that the improved TER method has higher imaging resolution and better defect identification effect. It can directly and clearly reflect the actual characteristics of the void defects behind the lining and effectively identify lining thickness, buried depth of steel bar, and specific locations and scopes of the voids behind and inside the lining. It can quantitatively describe 10-20 cm voids and locate and determine the magnitude of the voids less than 10 cm. Besides, it has a good reference for the identification result of the target body with a depth of more than 30 cm behind the lining. Meanwhile, the improved TER method is less disturbed by metal mediums and can accurately locate the void defects behind the lining with a void range greater than 30 cm in a wide range of continuous detection.

     

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