Tunnel lining structures are susceptible to internal defects over long-term service. As ground penetrating radar (GPR) enables continuous scanning and offers nondestructive, efficient inspection, it has become an important tool for detecting defects. Compared with traditional methods, intelligent detection methods can automatically learn representative features from GPR data and are better suited to dealing with strong noise, blurred defect boundaries, and other challenges encountered under complex operating conditions. This paper reviews intelligent detection technologies for tunnel lining structural defects based on GPR data. It systematically summarizes the signal characteristics of common internal defects and the methods used for dataset construction, and further reviews intelligent defect detection methods and quantitative defect assessment methods.Based on this review and analysis, the current limitations of existing studies are identified, and future research directions are discussed. This review aims to provide a reference for research and engineering applications of intelligent detection technologies for tunnel lining structural defects.
Zhou et al. (Mon,) studied this question.