Experimental GPR datasets to characterize multi-layered pavement structures-Tack coat evaluation using hybridization method
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View abstract on PubMed
Summary
This summary is machine-generated.This study uses impulse Ground Penetrating Radar (GPR) to analyze pavement layers and tack coat bonding. Machine learning models accurately map these features, improving infrastructure monitoring.
Area Of Science
- Civil Engineering
- Geophysics
- Materials Science
Background
- Non-destructive testing (NDT) is crucial for pavement verification and monitoring.
- Conventional Ground Penetrating Radar (GPR) struggles with thin pavement layers and tack coat characterization.
- Accurate assessment of tack coat is vital for ensuring proper bonding and pavement longevity.
Purpose Of The Study
- To develop and validate a method for characterizing tack coat layers in pavements using impulse GPR.
- To create a comprehensive database of pavement structures with controlled variations for research.
- To distinguish between areas with and without tack coat and detect subtle geometric variations.
Main Methods
- Impulse GPR with multiple central frequencies was used on controlled pavement structures.
- A database was created with variations in materials, geometries, and tack coat emulsion quantity.
- A hybrid Machine Learning/Full Waveform Inversion (FWI) approach was explored for data processing.
- Support Vector Machine (SVM) model was employed for data classification and mapping.
Main Results
- The impulse GPR system with ground-coupled bowtie antennas was effective in data acquisition.
- The SVM model successfully classified acquired data, distinguishing tack coat presence.
- Results were mapped as electromagnetic images, visualizing pavement layer characteristics.
- The methodology shows promise for enhanced pavement layer characterization.
Conclusions
- Impulse GPR, combined with machine learning, offers a viable solution for detailed pavement layer analysis.
- This approach enhances the capability to assess critical thin layers like tack coats.
- The developed methodology supports improved pavement design, construction quality control, and long-term monitoring.
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