Rapid Identification and Location of Defects behind Tunnel Lining Based on Ground-Penetrating Radar

Abstract

Ground-penetrating radar (GPR) is a mainstream tool to detect defects behind tunnel linings, but the difficulty in interpreting GPR signals limits its application. This paper proposes an intelligent way to differentiate the defects behind tunnel linings by means of a model test and feature parameter analysis, to achieve an efficient and accurate analysis of GPR signals. The model test reveals the differences between defect and non-defect GPR data in amplitude, signal entropy, standard deviation, and other feature parameters. The amplitude of the defect data was on average six times as large as that of non-defect data, and the signal entropy was about 1.2 times larger. The two feature parameters lay the basis for defect detection by GPR. On this basis, a GPR-based automatic identification method was proposed, and the program was compiled on MATLAB. The program achieved a defect recognition rate as high as 96% through a field test at a rapid speed. The program is highly accurate and feasible for detecting defects behind tunnel linings with the aid of GPR.