An Innovative Approach to Determine Rebar Depth and Size by Comparing GPR Data with a Theoretical Database

TL;DR

This paper introduces a novel algorithm that accurately determines rebar depth and size in concrete using GPR data by comparing extracted hyperbola signals with a theoretical database, overcoming signal extraction challenges.

Contribution

The paper presents an innovative method combining hyperbola signal processing and database comparison to simultaneously identify rebar depth and size from GPR data.

Findings

Successfully removes direct wave noise from GPR data

Accurately extracts hyperbola outlines from complex signals

Achieves 100% accuracy in depth and 95.11% in size determination

Abstract

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.