论文标题
通过将GPR数据与理论数据库进行比较来确定钢筋深度和大小的创新方法
An Innovative Approach to Determine Rebar Depth and Size by Comparing GPR Data with a Theoretical Database
论文作者
论文摘要
地面穿透雷达（GPR）是一种有效的技术，用于快速识别混凝土结构中的嵌入式钢筋。但是，由于难以从GPR数据中提取信号以及数据中显示的钢筋深度和大小之间的固有耦合，因此同时确定钢筋深度和大小具有挑战性。本文提出了一种创新算法来解决此问题。首先，来自GPR数据的双曲线信号是通过直接波去除，信号重建和分离来识别的。随后，数据库是由一系列理论双曲线开发的，然后与提取的双曲线轮廓进行了比较。最后，通过搜索数据库中最接近的对应物来确定钢筋深度和大小。获得的结果非常有前途，并表明：（1）实现本文中介绍的方法可以从GPR数据中完全消除直接波噪声，并可以成功地从交织的双曲线中提取大概； （2）所提出的方法可以同时确定钢筋深度和大小，精度分别为100％和95.11％。
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.
