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Spalling of concrete fragments due to the deterioration of concrete structures can cause property damage or serious and even fatal accidents; thus, there is a need to detect such deterioration. Generally, the hammering test is employed as the main inspection method to prevent such concrete spalling; however, it requires close contact with the structure being tested. Getting close to the structure for inspection is expensive and time consuming, and if the structure is high up, there is a risk of falling. Therefore, in this study, we developed a system for inspecting concrete structures without approaching them, using infrared thermography. In order to detect floating and delamination using infrared thermography, it is necessary to find temperature irregularities caused by such damage from an infrared image, but such an inspection method has not been realized so far. There are two main reasons for this. First, it is difficult to evaluate whether the concrete structure is in an appropriate temperature condition suitable for detecting the floating and delamination. Second, it is difficult to detect temperature irregularities caused by floating and delamination among the various causes of temperature irregularities. In this study, we resolved these issues by developing equipment to investigate whether the object is in an appropriate temperature condition for proper photography and by developing a machine learning-based method to automatically detect only the temperature irregularities caused by floating and delamination. By resolving these issues, we have developed a promising novel inspection method for the prevention of concrete spalling, which is reported in this article.

Development of a Concrete Floating and Delamination Detection System Using Infrared Thermography