The goal of the condition assessment of concrete structures is to gain an insight into current condition of concrete and the existence of defects, which decrease durability and usability of the structure. Defects are quite difficult to detect using infrared thermography when concrete elements cannot be thermally excited with the Sun, together with unfavorable thermophysical properties of concrete structures. In this paper, principal component thermography (PCT) is applied as a post-processing method to a sequence of thermograms in order to enhance defect detectability in concrete structures. Defects are detected by analyzing a set of empirical orthogonal functions (EOFs), which were acquired by applying principal component analysis to a sequence of thermograms. The research was performed using concrete samples containing known defects, which were tested using a step heating thermography setup. The results of presented research show that PCT is an effective post-processing method to improve defect detection in concrete structures. By effectively improving the defect detection, PCT has a potential to improve the non-destructive testing (NDT) accuracy of using infrared thermography (IRT) on concrete structures, especially in shaded areas of such structures. The research also shows the defect detectability depending on concrete type thermal excitation setup and defect geometry.
Effects of Ambient Temperature and Relative Humidity on Subsurface Defect Detection in Concrete Structures by Active Thermal Imaging
