Open Access Open Access  Restricted Access Subscription or Fee Access

Exploration of the Factors Affecting Ground Penetrating Radar Response in Bridge Inspection Applications


(*) Corresponding author


Authors' affiliations


DOI: https://doi.org/10.15866/irece.v12i3.19473

Abstract


Ground Penetrating Radar (GPR) is a nondestructive evaluation technique that is recently employed in various civil engineering applications such as concrete quality evaluations, locating reinforcing rebar, and bridge deck integrity assessments. Previous research has shown that the chloride and moisture content of concrete, corrosion state, and depth of reflecting objects (e.g., steel reinforcing bars) have some impact on the strength of GPR signals. What is not yet clear, however, is to what extent these factors can affect GPR response. This research has sought to quantitatively determine the effects of these factors on the attenuation and the resulting response of GPR signals reflected from reinforcing bars in concrete. The effects of these factors were experimentally demonstrated by analyzing data from four reinforced concrete slabs. Analysis of the processed data showed that attenuation was highly attributed to the depth of the reinforcing bars as compared to the concrete chloride and moisture content, where the amplitude of the reflected signals decreased by 4.5dB for every 25 mm increase in depth as compared to about 1.0 dB reduction in signal amplitude due to the presence of chloride and moisture. Corrosion of reinforcement bars, on the other hand, slightly increased the amplitude of the reflected signals by 1.0 dB.
Copyright © 2021 Praise Worthy Prize - All rights reserved.

Keywords


Ground Penetrating Radar; Signal Strength; GPR Signal Attenuation; Steel Corrosion; Chloride & Moisture

Full Text:

PDF


References


Alsharqawi, M., Zayed, T. and Shami, A. (2020), Ground penetrating radar-based deterioration assessment of RC bridge decks, Construction Innovation, Vol. 20 No. 1, pp. 1-17.
https://doi.org/10.1108/ci-08-2019-0076

Goulias, D., et al., Condition Assessment of Bridge Decks through Ground-Penetrating Radar in Bridge Management Systems, Journal of Performance of Constructed Facilities 2020. 34(5): p. 04020100.
https://doi.org/10.1061/(asce)cf.1943-5509.0001507

Bianchini Ciampoli L, Tosti F, Economou N, Benedetto F. Signal Processing of GPR Data for Road Surveys. Geosciences. 2019; 9(2):96.
https://doi.org/10.3390/geosciences9020096

Senin, S., et al. Damage detection of artificial corroded rebars and quantification using non-destructive methods on reinforced concrete structure. in Journal of Physics: Conference Series. 2019. IOP Publishing.
https://doi.org/10.1088/1742-6596/1349/1/012044

Varnavina, A.V., et al., Data acquisition and processing parameters for concrete bridge deck condition assessment using ground-coupled ground penetrating radar: Some considerations. Journal of Applied Geophysics, 2015. 114: p. 123-133.
https://doi.org/10.1016/j.jappgeo.2015.01.011

Sultan, A.A., Advancements in evaluating reliability of nondestructive technologies for the detection of subsurface fracture damage in RC bridge decks, in Civil & Environmental Engineering. 2017, University of Missouri - Columbia: USA.
https://doi.org/10.32469/10355/65442

Sossa V, Pérez-Gracia V, González-Drigo R, A. Rasol M. Lab Non Destructive Test to Analyze the Effect of Corrosion on Ground Penetrating Radar Scans. Remote Sensing. 2019; 11(23):2814.
https://doi.org/10.3390/rs11232814

Garcia-Fernandez, M., et al. Gpr system onboard a uav for non-invasive detection of buried objects. in 2018 IEEE International Symposium on Antennas and Propagation & USNC/URSI National Radio Science Meeting. 2018. IEEE.
https://doi.org/10.1109/apusncursinrsm.2018.8608907

M. González-Díaz, M. García-Fernández, Y. Álvarez-López and F. Las-Heras, Improvement of GPR SAR-Based Techniques for Accurate Detection and Imaging of Buried Objects, in IEEE Transactions on Instrumentation and Measurement, vol. 69, no. 6, pp. 3126-3138, June 2020.
https://doi.org/10.1109/tim.2019.2930159

Pham, M.-T. and S. Lefèvre. Buried object detection from B-scan ground penetrating radar data using Faster-RCNN. in IGARSS 2018-2018 IEEE International Geoscience and Remote Sensing Symposium. 2018. IEEE.
https://doi.org/10.1109/igarss.2018.8517683

Zhou F, Chen Z, Liu H, Cui J, Spencer BF, Fang G. Simultaneous Estimation of Rebar Diameter and Cover Thickness by a GPR-EMI Dual Sensor. Sensors. 2018; 18(9):2969.
https://doi.org/10.3390/s18092969

Xiang, Z., A. Rashidi, and G. Ou, An Improved Convolutional Neural Network System for Automatically Detecting Rebar in GPR Data, in Computing in Civil Engineering 2019: Data, Sensing, and Analytics. 2019, American Society of Civil Engineers Reston, VA. p. 422-429.
https://doi.org/10.1061/9780784482438.054

Dinh, K., N. Gucunski, and T.H.J.A.i.C. Duong, An algorithm for automatic localization and detection of rebars from GPR data of concrete bridge decks, Automation in Construction, 2018. 89: p. 292-298.
https://doi.org/10.1016/j.autcon.2018.02.017

Shamir O, Goldshleger N, Basson U, Reshef M. Laboratory Measurements of Subsurface Spatial Moisture Content by Ground-Penetrating Radar (GPR) Diffraction and Reflection Imaging of Agricultural Soils. Remote Sensing. 2018; 10(10):1667.
https://doi.org/10.3390/rs10101667

Klotzsche, A., Jonard, F., Looms, M., van der Kruk, J. and Huisman, J. (2018), Measuring Soil Water Content with Ground Penetrating Radar: A Decade of Progress. Vadose Zone Journal, 17: 1-9 180052.
https://doi.org/10.2136/vzj2018.03.0052

El-Zahab, S., Zayed, T. Leak detection in water distribution networks: an introductory overview. Smart Water 4, 5 (2019).
https://doi.org/10.1186/s40713-019-0017-x

Senin, S., et al., Locating Underground Water Pipe Leakages Via Interpretation of Ground Penetrating Radar Signals, International Journal of Engineering & Technology 2019. 8(2): p. 72-77.

Amran, T., et al. Monitoring underground water leakage pattern by ground penetrating radar (GPR) using 800 MHz antenna frequency. in IOP Conference Series: Materials Science and Engineering. 2018.
https://doi.org/10.1088/1757-899x/298/1/012002

Trinks, I., et al., Large-area high-resolution ground-penetrating radar measurements for archaeological prospection. Archaeological Prospection, 2018. 25(3): p. 171-195.
https://doi.org/10.1002/arp.1599

Qin, T., et al., Underwater archaeological investigation using ground penetrating radar: A case analysis of Shanglinhu Yue Kiln sites (China), Journal of Applied Geophysics, 2018. 154: p. 11-19.
https://doi.org/10.1016/j.jappgeo.2018.04.018

Imposa, S., et al., New data on buried archaeological ruins in Messina area (Sicily-Italy) from a ground penetrating radar survey, Journal of Archaeological Science: Reports 2018. 17: p. 358-365.
https://doi.org/10.1016/j.jasrep.2017.11.031

Ahmed, S.B., et al., Mapping the possible buried archaeological targets using magnetic and ground penetrating radar data, Fayoum, Egypt, The Egyptian Journal of Remote Sensing and Space Science, 2019.
https://doi.org/10.1016/j.ejrs.2019.07.005

Tosti, F., et al., An experimental-based model for the assessment of the mechanical properties of road pavements using ground-penetrating radar, Construction and Building Materials 2018. 165: p. 966-974.
https://doi.org/10.1016/j.conbuildmat.2018.01.179

Tong, Z., et al., Pavement-distress detection using ground-penetrating radar and network in networks, Construction and Building Materials 2020. 233: p. 117352.
https://doi.org/10.1016/j.conbuildmat.2019.117352

Wang, S., et al., Continuous real-time monitoring of flexible pavement layer density and thickness using ground penetrating radar, NDT & E International 2018. 100: p. 48-54.
https://doi.org/10.1016/j.ndteint.2018.08.005

Travassos, X.L., et al., Artificial neural networks and machine learning techniques applied to ground penetrating radar: A review, Applied Computing and Informatics 2020.
https://doi.org/10.1016/j.aci.2018.10.001

Ishitsuka, K., et al., Object detection in ground-penetrating radar images using a deep convolutional neural network and image set preparation by migration, International Journal of Geophysics, 2018.
https://doi.org/10.1155/2018/9365184

Kafedziski, V., S. Pecov, and D. Tanevski. Detection and classification of land mines from ground penetrating radar data using faster R-CNN. in 2018 26th Telecommunications Forum (TELFOR). 2018. IEEE.
https://doi.org/10.1109/telfor.2018.8612117

Zheng, J., et al., Convolutional Neural Networks for Water Content Classification and Prediction With Ground Penetrating Radar, IEEE Access 2019. 7: p. 185385-185392.
https://doi.org/10.1109/access.2019.2960768

I. Giannakis, A. Giannopoulos and C. Warren, A Machine Learning Scheme for Estimating the Diameter of Reinforcing Bars Using Ground Penetrating Radar, in IEEE Geoscience and Remote Sensing Letters, vol. 18, no. 3, pp. 461-465, March 2021.
https://doi.org/10.1109/lgrs.2020.2977505

Asadi, P., Gindy, M. & 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 23, 2618–2627 (2019).
https://doi.org/10.1007/s12205-019-2012-z

M. Sun, J. Pan, C. Le Bastard, Y. Wang and J. Li, Advanced Signal Processing Methods for Ground-Penetrating Radar: Applications to Civil Engineering, in IEEE Signal Processing Magazine, vol. 36, no. 4, pp. 74-84, July 2019.
https://doi.org/10.1109/msp.2019.2900454

Tarussov, A., et al., Condition assessment of concrete structures using a new analysis method: Ground-penetrating radar computer-assisted visual interpretation, Construction and Building Materials, 2013. 38: p. 1246-1254.
https://doi.org/10.1016/j.conbuildmat.2012.05.026

Institute, A.-A.C., 228: 2R-13 Report on nondestructive test methods for evaluation of concrete in structures. 2013, ACI Publications Detroit, United States.

Romero, F.A., et al., Validation of Benefits of Automated Depth Correction Method for Improving Accuracy of GPR Deck Deterioration Maps. Transportation Research Record: Journal of the Transportation Research Board, 2015(2522): p. 100-109.
https://doi.org/10.3141/2522-10

Dinha, K., et al. Attenuation-based Methodology for Condition Assessment of Concrete Bridge Decks using GPR. in ISARC. Proceedings of the International Symposium on Automation and Robotics in Construction. 2015. Vilnius Gediminas Technical University, Department of Construction Economics & Property.
https://doi.org/10.22260/isarc2015/0055

He, X.-Q., et al. Review of GPR rebar detection. in PIERS proceedings. 2009.

Ghani, A.H.A., S.F. Senin, and R.J.J.T. Hamid, Attenuation of ground penetrating radar signal amplitude in monitoring reinforced steel corrosion. Jurnal Teknologi 2013. 65(2).
https://doi.org/10.11113/jt.v65.2194

Raju, R.K., M.I. Hasan, and N.J.A.M.J. Yazdani, Quantitative Relationship Involving Reinforcing Bar Corrosion and Ground-Penetrating Radar Amplitude, Materials Journal 2018. 115(3).
https://doi.org/10.14359/51702187

Solla, M., et al., Assessing Rebar Corrosion through the Combination of Nondestructive GPR and IRT Methodologies, Remote Sensing, 2019. 11(14): p. 1705.
https://doi.org/10.3390/rs11141705

Al Qurishee, M., et al., Non-Destructive Test Application in Civil Infrastructure, International Research Journal of Engineering and Technology (IRJET) 2019.

ASTM, Standard Test Method for Evaluating Asphalt-Covered Concrete Bridge Decks Using Ground Penetrating Radar, in ASTM D6087-08(2015)e1. 2015, ASTM International,: West Conshohocken, PA.
https://doi.org/10.1520/d6087-05

Martino, N., et al., Determining Ground Penetrating Radar Amplitude Thresholds for the Corrosion State of Reinforced Concrete Bridge Decks. Journal of Environmental and Engineering Geophysics, 2014. 19(3): p. 175-181.
https://doi.org/10.2113/jeeg19.3.175

Martino, N., et al., Quantifying Bridge Deck Corrosion Using Ground Penetrating Radar. Research in Nondestructive Evaluation, 2016. 27(2): p. 112-124.
https://doi.org/10.1080/09349847.2015.1067342

Wamweya, A., Application of ground penetrating radar (GPR) for bridge deck condition assessment: using a 1.5 GHz ground-coupled antenna. 2009.
https://doi.org/10.3997/2214-4609-pdb.157.sageep073

Sultan, A.A. and G.A.J.J.o.B.E. Washer, Reliability analysis of ground-penetrating radar for the detection of subsurface delamination, Journal of Bridge Engineering, 2018. 23(2): p. 04017131.
https://doi.org/10.1061/(asce)be.1943-5592.0001182


Refbacks

  • There are currently no refbacks.



Please send any question about this web site to info@praiseworthyprize.com
Copyright © 2005-2024 Praise Worthy Prize