An Innovative Approach to Determine Rebar Depth and Size by Comparing GPR Data with a Theoretical Database
This addresses the problem of accurately assessing concrete structures for engineers and inspectors, representing a strong specific gain in a domain-specific application.
The paper tackled the challenge of simultaneously determining rebar depth and size from ground penetrating radar (GPR) data by proposing an algorithm that extracts hyperbola signals and compares them with a theoretical database, achieving accuracies of 100% for depth and 95.11% for size.
Ground penetrating radar (GPR) is an efficient technique used for rapidly recognizing embedded rebar in concrete structures. However, due to the difficulty in extracting signals from GPR data and the intrinsic coupling between the rebar depth and size showing in the data, simultaneously determining rebar depth and size is challenging. This paper proposes an innovative algorithm to address this issue. First, the hyperbola signal from the GPR data is identified by direct wave removal, signal reconstruction and separation. Subsequently, a database is developed from a series of theoretical hyperbolas and then compared with the extracted hyperbola outlines. Finally, the rebar depth and size are determined by searching for the closest counterpart in the database. The obtained results are very promising and indicate that: (1) implementing the method presented in this paper can completely remove the direct wave noise from the GPR data, and can successfully extract the outlines from the interlaced hyperbolas; and (2) the proposed method can simultaneously determine the rebar depth and size with the accuracy of 100% and 95.11%, respectively.