Masking effect of surface coatings in long pulsed thermography: A quantitative analysis of thickness discrimination

Active thermography is a powerful non-destructive evaluation (NDE) technique for characterizing materials and detecting defects. A common practice to enhance measurement reliability is the application of a high-emissivity paint coating. However, this coating can introduce a thermal barrier, potentially masking the intrinsic thermal response of the underlying substrate, which is critical for tasks such as thickness discrimination. This study provides a quantitative analysis of the masking effect induced by a black paint coating on the transient thermal response of steel samples of varying thicknesses, as measured by laser-long pulse active thermography. We employ a combined approach of analytical modeling, numerical simulation, and experimental validation. The analysis is grounded in the one-dimensional heat conduction equation, with a lumped-parameter model used to explore the system’s primary dynamics. Experimental tests on a multi-thickness steel block provide validation data. Our findings reveal that the low thermal diffusivity of the paint layer creates a significant initial thermal transient that can obscure the thickness-dependent response of the substrate. This masking effect is particularly pronounced for thicker coatings and substrates. We demonstrate that spatial averaging of the thermal data can partially mitigate this effect, restoring thickness discrimination for substrates up to a certain thickness threshold. The study concludes that while emissivity-enhancing coatings are beneficial, their thermal properties must be carefully considered in the design and interpretation of long pulsed thermography experiments. We propose practical guidelines for optimizing coating selection and data analysis strategies to preserve the integrity of NDE measurements.