Abstract
The article continues the study on determining the possibility of applying ground penetrating radar (GPR) technologies in the road construction industry. The authors conduct research using an antenna unit that registers the cross-polarisation component of the reflected signal. In this case, processing the obtained radar images comes down to subtracting two mutually orthogonal components of the signal, which allows the determination of areas of the environment with anisotropic properties. Identifying and positioning extraneous inclusions, finding communications, and determining the location of reinforcement in roadway and bridge structures are relevant tasks. Their solution lies in studying the phenomenon of wave diffraction on extraneous inclusions of the investigated environment. Metal inclusions of different diameters are distinctly visible on radar images obtained during laboratory research. The laboratory studies conducted by the authors showed that the shape and nature of the hyperbola of the diffracted wave significantly depend on the object’s depth, diameter, and material. Therefore, further research in this direction should aim at studying the shape of the diffracted wave, which ultimately allows for judging the depth of occurrence and the diameter of a local extraneous inclusion. When finding and identifying reinforcement in structural layers of road surfaces and elements of bridges, difficulties arise due to the spacing of the reinforcing mesh. With a small reinforcing mesh spacing, when the wavelength is longer than the spacing, the reflections from the adjacent reinforcement bars merge into a common continuous boundary and make the lower layers of the structure almost indistinguishable. Solving the mentioned difficulties is possible by improving the equipment base and the algorithms for processing and interpreting the received radar images. Completed theoretical studies and computational experiments allow us to state that the development of road surface thickness measurement and defect detection techniques will become the basis of the road surface monitoring system using the subsurface geolocation method. Keywords: ground penetrating radar, radar image, road surface, dielectric constant, defect detection, thickness measurement, local inclusions.
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