Optimization Algorithm to Determine Thermal Parameters for Defect Depth Estimation

Infrared Thermography (IRT) is one of the non-destructive evaluation techniques used to detect defects in a structure based on temperature differences due to the presence of air voids. Depth estimation of the defects can be done by various post-processing methods after obtaining thermograms over a period of time. Most prevalent methods require knowledge of the thermal properties of the sound area, which is typically challenging to ascertain in the field. Based on the experimental surface temperature response of the sound area in the field specimen, this study endeavors to estimate the unknown parameters of the specimen. This inverse heat transfer problem is done by updating a finite element model with a trust region reflective algorithm. The experiment is conducted by heating a GFRP-wrapped surface of a concrete slab with halogen lamps, and subsequently recording the transient response of the surface temperature with a thermal camera. The thermal properties of concrete and GFRP were estimated using the proposed algorithm, which closely matched actual physical values.