ABSTRACT
Realizing automatic and intelligent detection and identification of highway subgrade diseases provides important technical support for highway maintenance. In this paper, the highway data collected by GPR are processed to interpret and recognize the disease characteristics of GPR images. The GprMax software is used to carry out forward simulation of highway cavities and water-rich zones by setting the parameters such as dielectric constant, conductivity, disease size, and depth of different diseases, and carry out comparative experiments on cavities and water-rich zones of different sizes and depths, to determine the image characteristics of diseases and provide an important reference basis for GPR image interpretation. We use GprMax software to interpret the 3D ground penetrating radar data and identify the diseases such as highway cavities, cracks, ruts, water-rich zones, and looseness, providing data support for highway maintenance.
