# Detecting Reinforced Concrete Rebars Using Ground Penetrating Radars
###### Abstract  
A new algorithm is developed to automatically detect rebar locations and diameters of reinforced concrete structures using the ground penetrating radar technique. The study uses two-way travel time and biquadratic equations to formulate electromagnetic wave speed in reinforced concrete structures where hyperbolic signatures are approximated. Leveraging an established algorithm, a computer code has been developed to offer automated analysis of ground-penetrating radar data obtained from survey grids. Four reinforced concrete slabs were designed, fabricated, and tested to validate the developed evaluation approach. The proposed methodology demonstrates outstanding signal processing proficiency and reliably and effectively identifies rebar information. nodestructive evaluation; ground-penetrating radar; rebar depth; rebar diameter; reinforced-concrete structures +
Footnote †: journal: Applied  
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Footnote †: journal: Applied  
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Footnote 1: College of Engineering and Computer Sciences, Marshall University, Huntington, WW 25755, USA 1  
concrete structures since the early 1990s. This technique was applied to monitor and evaluate bridge decks [21], to detect rebar size and location in the concrete structures [22; 23; 24], and to estimate the concrete cover and thickness of the bridge deck [25; 26; 27]. The GPR method has also been widely used for concrete moisture evaluation [28], deterioration mapping of old bridge decks [29], tracking cracks [30], assessment of rebar corrosion in concrete slabs [31; 32], detection of embedded defects [33], detection voids in grouted post-tensioned concrete ducts [34], investigation of concrete mix variations and environmental conditions on defect detection [35], identification of corrosion-induced anomalies of bridge decks [36], rebar detection [37], visualization defects of fiber-reinforced polymer-wrapped reinforced concrete slabs [38; 39; 40], and mapping rebar layers [41]. The environmental factors affecting the GPR signal were also investigated [42], and new techniques were applied in GPR signal processing [43]. [PERSON] et al. [44] proposed a method based on a synthetic aperture focusing technique to determine the rebar depth and spacing. [PERSON] et al. [45] introduced a physical model that accounts for the electromagnetic signature of a buried reinforcing steel bar, considering the rebar's radius. The GPR radargrams underwent several digital image processing stages, with subsequent analysis of power reflectivity variations within the energy zone as the GPR antenna traversed the reinforced concrete surface. Power reflectivity data was generated for vertically oriented migration traces. Calculating the radius of the reinforcing steel bar, considering the distances and the long-dimension radius of an energy footprint. [PERSON] and [PERSON] [46] correlated the rebar depth and size with the signal amplitude, but the results indicated that the method's accuracy was low. [PERSON] and [PERSON] [47] compared discrete and stationary wavelet transforms by creating a contour map of stationary wavelet transform detail coefficients. A conclusion was made that the stationary wavelet transform proves to be an effective method for measuring the diameter of a steel bar. [PERSON] et al. [48] proposed a new method mainly focusing on automatically searching the locations of rebans in RC structures based on the modified existing hyperbolic signatures model. This method can efficiently detect embedded objects with the assumption of zero diameter of the rebars. [PERSON] et al. [49; 50] presented an integrated approach based on pattern recognition and curve fitting principles to determine the rebar's horizontal location, depth, and size simultaneously. This approach has a few limitations. Firstly, extracting precise points of interest from hyperbolas remains challenging, especially in environments with high noise levels. Secondly, estimating electromagnetic wave velocity based on imaginary curves is prone to errors.