Cover Thickness Prediction for Steel inside the Concrete by Sub-Terahertz waves using Deep Learning

Abstract

Reinforced concrete, characterized by the placement of steel reinforcement inside the concrete, is one of the most widely used structural forms in building construction. The necessity of maintaining old buildings has risen and hence, studies have explored potential of Sub-Terahertz waves, a type of electromagnetic waves that fall between the radio wave and the light wave frequencies for non-destructive testing. This paper proposed a method that applies Deep Learning in estimation of the cover thickness, defined as the distance from the embedded steel plate to the concrete surface, using Sub-Terahertz. It also focused on expanding the measurable range of the Sub-Terahertz waves. The results showed a recall of over 80% on average with cover thickness of 10mm to 40mm. Furthermore, an analysis using SHAP revealed that the interpretation of the results varied depending on the frequency and cover thickness used for the measurements.