Study on Estimation of Internal Cracks in Reinforced Concrete by Electromagnetic Waves Using Machine Learning

Abstract

Due to the current problems of deterioration of reinforced concrete structures and the shortage and population aging of engineers, there is a demand for methods that allow non-skilled engineers to quantitatively inspect reinforced concrete structures. In this study, by using electromagnetic wave radar, which is relatively easy to detect reinforcing bars and internal cracks, the estimation of microcracking in concrete at the early stage of deterioration was investigated using machine learning. As a result of the study, using the image extracted only the part of reinforcement from data measured by the electromagnetic radar, it was shown that it is possible to estimate cracks with about 0.04nnn width by learning and judging those images with the convolutional neural network.