Abstract
Ground-penetrating radar (GPR) is a promising non-destructive technique to be applied on monitoring the density change during asphalt pavement compaction. The utmost challenge of this application is the unknown effect of surface moisture, sprayed by the compactor during compaction, on GPR signals. To extract density information without the effect of surface moisture, a correction algorithm based on reference scan approach was developed. To evaluate the performance of the algorithm, a full-scale test site was constructed with compaction pass number from 0 to 10, and a large amount of GPR data were collected from the pavement with different surface moisture contents. A total of 22 cores were extracted for validation purposes. After applying the algorithm, it was found that the average density prediction error was reduced significantly. By using correction algorithm together with the density model, the density of asphalt pavement was obtained with high accuracy.
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