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A Fast and Robust Method for Estimating the Parameters of Ground Penetrating Radar Waves of Concrete Structures

  • ELECTROMAGNETIC METHODS
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Abstract

The received signals in ground penetrating radar (GPR) techniques contain very valuable information on the size and orientation of the reflectors as well as the properties of the propagation path of the electromagnetic wave. Sometimes, these signals contain many overlapping reflected echoes due to the complexity of the studied geometry. Accurate estimation of these echoes is essential for the non-destructive evaluation of reinforced concrete structures. In this study, the matching pursuit (MP) algorithm is used to decompose the GPR signal into multiple echoes. The selection of the appropriate atoms is done by teaching learning based optimization (TLBO) algorithms which, at the same time, change five parameters (bandwidth, arrival time, center frequency, amplitude and phase), until a good representation of the original GPR signal is achieved. The effectiveness of the proposed method is tested using both synthetic signals generated from a gprMax simulation program, and a real data collected on a concrete slab specimen at different offset.

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REFERENCES

  1. Benedetto, A. and Pajewski, L., Civil Engineering Applications of Ground Penetrating Radar, Berlin: Springer, 2015.

    Book  Google Scholar 

  2. Wu Hai-Kuan, Zhi-Le, S., Chang-Wu, L., Yi-Chen, M., and Bao-Xian, L., Experimental research on the detection of inner defects of bellows based on ground penetrating radar, Russ. J. Nondestruct. Test., 2020, vol. 56, no. 6, pp. 516–526.

    Article  Google Scholar 

  3. Wai-Lok Lai, W., Dérobert, X., and Annan, P., A review of ground penetrating radar application in civil engineering: A 30-year journey from locating and testing to imaging and diagnosis, NDT&E Int., 2018, vol. 96, pp. 58–78.

    Article  Google Scholar 

  4. Sbartaï, Z.M., Laurens, S., Balayssac, J.P., Arliguie, G., and Ballivy, G., Ability of the direct wave of radar ground-coupled antenna for NDT of concrete structures, NDT&E Int., 2006, vol. 39, no. 5, pp. 400–407.

    Article  Google Scholar 

  5. Wang, X. and Liu, S., Noise suppressing and direct wave arrivals removal in GPR data based on Shearlet transform, Signal Proces., 2017, vol. 132, pp. 227–242.

    Article  Google Scholar 

  6. Qin, Y., Qiao, L.H., Ren, X.Z., and Wang, Q.F., Using bidimensional empirical mode decomposition method to identification buried objects from GPR B-scan image, 16th Int. Conf. Ground Penetrating Radar (GPR), Hong Kong, 2016.

  7. Li, J., Liu, C., Zeng, Z., and Chen, L., GPR signal denoising and target extraction with the CEEMD method, IEEE Geosci. Remote Sens. Lett., 2015, vol. 12, no. 8, pp. 1–5.

    Google Scholar 

  8. Liu, C., Song, C., and Lu, Q., Random noise de-noising and direct wave eliminating based on SVD method for ground penetrating radar signals, 16th Int. Conf. Ground Penetrating Radar (GPR), Hong Kong, 2016.

  9. Kilic, G. and Eren, L., Neural network based inspection of voids and karst conduits in hydro–electric power station tunnels using GPR, J. Appl. Geophys., 2018, vol. 151, pp. 194–204.

    Article  Google Scholar 

  10. Zhang, J., Yang, X., Li, W., Zhang, S., and Jia, Y., Automatic detection of moisture damages in asphalt pavements from GPR data with deep CNN and IRS method, Autom. Constr., 2020, vol. 113.

    Book  Google Scholar 

  11. Liu, H., Lin, C., Cui, J., Fan, L., Xie, X., and Spencer, B.F., Detection and localization of rebar in concrete by deep learning using ground penetrating radar, Autom. Constr., 2020, vol. 118.

    Book  Google Scholar 

  12. Asadi, P., Gindy, M., and Alvarez, M., A machine learning based approach for automatic rebar detection and quantification of deterioration in concrete bridge deck ground penetrating radar B-scan images, KSCE J. Civ. Eng., 2019, vol. 23, pp. 2618–2627.

    Article  Google Scholar 

  13. Giannakis, I., Giannopoulos, A., and Warren, C., A machine learning scheme for estimating the diameter of reinforcing bars using ground penetrating radar, IEEE Geosci. Remote Sens. Lett., 2021, vol. 18, no. 3, pp. 461–465.

    Article  Google Scholar 

  14. Giannakis, I., Giannopoulos, A., Warren, C., and Sofroniou, A., Fractal-constrained crosshole/borehole-to-surface full-waveform inversion for hydrogeological applications using ground-penetrating radar, IEEE Trans. Geosci. Remote Sens., 2022, vol. 60, pp. 1–10.

    Article  Google Scholar 

  15. Mallat, S.G. and Zhang, Z., Matching pursuits with time-frequency dictionaries, IEEE Trans. Signal Process., 1993, vol. 41, no. 12, pp. 3397–3415.

    Article  Google Scholar 

  16. Zhang, Q., Yang, G., and Que, P., Ultrasonic signals processing base on parameters estimation, Russ. J. Nondestr. Test., 2009, vol. 45, no. 1, pp. 61–66.

    Article  Google Scholar 

  17. Yacef, N., Bouden, T., and Grimes, M., Accurate ultrasonic measurement technique for crack sizing using envelope detection and differential evolution, NDT&E Int., 2019, vol. 102, pp. 161–168.

    Article  Google Scholar 

  18. Rao, R.V., Savsani, V.J., and Vakharia, D.P., Teaching-learning-based optimization: an optimization method for continuous non-linear large scale problems, Inf. Sci. (Ny)., 2012, vol. 183, no. 1.

  19. Giannopoulos, A., Modelling ground penetrating radar by GprMax, Constr. Build. Mater., 2005, vol. 19, no. 10.

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Correspondence to Morad Grimes.

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Kemache, N., Hacib, T., Grimes, M. et al. A Fast and Robust Method for Estimating the Parameters of Ground Penetrating Radar Waves of Concrete Structures. Russ J Nondestruct Test 59, 381–391 (2023). https://doi.org/10.1134/S1061830923600090

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  • DOI: https://doi.org/10.1134/S1061830923600090

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