Deterioration of concrete structures has become a widespread problem with high repair costs. The corrosion of rebar is one of the major causes. GPR has potential for rebar corrosion detection. But the rapid survey generates a large amount of data, which require an automatic approach for effective data processing and information extraction. This paper proposes an automatic process to effectively extract the rebar reflection in the radargram image and estimate the concrete condition above the rebar. The process uses template matching to locate the hyperbola position, image processing to extract hyperbolic region, and algebraic fitting to rapidly estimate hyperbola parameters. The estimated parameters can be used to calculate the wave propagation velocity and relative permittivity in concrete above the rebar, which can be used to further evaluate the concrete condition. The effectiveness of the proposed method is validated using experiment testing.
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ASME 2012 Conference on Smart Materials, Adaptive Structures and Intelligent Systems
September 19–21, 2012
Stone Mountain, Georgia, USA
Conference Sponsors:
- Aerospace Division
ISBN:
978-0-7918-4509-7
PROCEEDINGS PAPER
Automatic Extraction of Hyperbolic Signatures in Ground Penetrating Radar Images
Zhenhua Xie,
Zhenhua Xie
Georgia Institute of Technology, Atlanta, GA
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Xiangmin Wei,
Xiangmin Wei
Georgia Institute of Technology, Atlanta, GA
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Ying Zhang
Ying Zhang
Georgia Institute of Technology, Atlanta, GA
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Zhenhua Xie
Georgia Institute of Technology, Atlanta, GA
Xiangmin Wei
Georgia Institute of Technology, Atlanta, GA
Ying Zhang
Georgia Institute of Technology, Atlanta, GA
Paper No:
SMASIS2012-8153, pp. 855-860; 6 pages
Published Online:
July 24, 2013
Citation
Xie, Z, Wei, X, & Zhang, Y. "Automatic Extraction of Hyperbolic Signatures in Ground Penetrating Radar Images." Proceedings of the ASME 2012 Conference on Smart Materials, Adaptive Structures and Intelligent Systems. Volume 1: Development and Characterization of Multifunctional Materials; Modeling, Simulation and Control of Adaptive Systems; Structural Health Monitoring. Stone Mountain, Georgia, USA. September 19–21, 2012. pp. 855-860. ASME. https://doi.org/10.1115/SMASIS2012-8153
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