Abstract
Ground-penetrating radar (GPR) is a prominent non-destructive testing (NDT) method for corrosivity evaluation in concrete structures. Most GPR interpretation methods rely solely on the absolute values of rebar reflection intensity, making them vulnerable to misinterpretation of the effects of complex factors. This study introduces a more comprehensive GPR data interpretation method, encompassing analysis in time and time-frequency domains. The developed method constitutes efficient GPR data collection and pre-processing, deep learning rebar recognition, and frequency domain analysis using the Short-Time Fourier Transform (STFT). The center frequency of rebar responses was normalized and depth-corrected to standardize the analysis method. The GPR condition mapping thresholds were optimized and validated using ground truth conditions from hammer tapping and reinforcement exposure of reinforced concrete walls. The method demonstrated superior performance compared to the traditional amplitude-based approach in detecting and quantifying the extent of corrosion-induced deterioration, with an average accuracy of 0.80 for active corrosion and 0.84 for active-corrosion with corrosion-induced delamination.
| Original language | English |
|---|---|
| Article number | e42641 |
| Journal | Heliyon |
| Volume | 11 |
| Issue number | 4 |
| DOIs | |
| Publication status | Published - 28 Feb 2025 |
Keywords
- Corrosion
- Ground penetrating radar
- Non-destructive testing
- Reinforced concrete structure
- Short-time fourier transform
ASJC Scopus subject areas
- General
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