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Ground Penetrating Radar Data Processing for Concrete Bridge Deck Evaluation

Sepehr Pashoutani, University of Nebraska - Lincoln


Ground penetrating RADAR (GPR) is a widely used nondestructive testing (NDT) method for bridge deck evaluation. However, it is still a challenging task for many GPR users to interpret and analyze the large amount of data collected from GPR surveys on bridges. Current GPR data processing algorithms do not provide comprehensive information about bridge deck condition. The objective of this dissertation is to provide a complete and quantitative analysis procedure of GPR data for the condition assessment of concrete bridge decks with or without overlays. Most GPR analysis methods use signal amplitude information to evaluate the deterioration of concrete bridge decks. In this study, a series of algorithms were developed to automatically extract three types of parameters from GPR signals: direct-coupling wave amplitude on the deck surface, wave velocity in cover concrete, and depth-corrected GPR signal amplitude from rebar reflections. Each parameter may reflect defects at different depths of the bridge deck, and differentiate surface defects from concrete deterioration and rebar corrosion. The developed GPR data analysis algorithms include preprocessing of GPR B-scans, wave velocity calculation using migration, automatic detection of rebar reflections, amplitude normalization, and depth-correction with actual rebar depth. Rebars are detected using a region-based object detection algorithm that relies on a filtering convolutional autoencoder and a convolutional neural network classifier. Wave velocity is estimated by optimizing the performance of migration over a range of possible electromagnetic wave velocities in concrete. Wave velocity is used to calculate the cover thickness map and perform depth-correction with actual rebar depth instead of two-way travel time. It is important to establish a proper threshold value for the GPR attenuation map to determine the deterioration regions and percentage of deck area that needs repair. Machine learning algorithms were proposed to correlate the GPR data with other NDT results (half-cell potential, vertical electrical impedance) to determine threshold values for GPR attenuation analysis.

Subject Area

Civil engineering

Recommended Citation

Pashoutani, Sepehr, "Ground Penetrating Radar Data Processing for Concrete Bridge Deck Evaluation" (2022). ETD collection for University of Nebraska-Lincoln. AAI30000775.