Differential Evolution-Based Estimation of Material Thermal Diffusivity from Pulsed Infrared Thermography

We investigate a strategy based on differential evolution (DE) optimization as a method for estimation of material thermal diffusivity from nondestructive one-sided pulsed infrared thermography (PIT) measurements. Diffusivity is a function of material thermal conductivity, density, and heat capacity. Local changes in thermal diffusivity could be associated with material degradation. PIT involves measuring transient material response to rapid thermal flash deposition on material surface. As heat diffuses, the surface temperature begins to decay until reaching the steady-state value. Surface temperature transients can be measured with a fast frame infrared camera. There exists an analytic solution as an infinite sum of power series for surface temperature transients in a plate, depending on thermal diffusivity and material thickness. Fitting the analytic solution to the PIT experimental data for a plate of known thickness allows to estimate thermal diffusivity. We utilize the DE optimization to solve the inverse problem of thermal diffusivity estimation for materials under test. The single-objective algorithm performs continuous optimization, minimizing error over each iteration. Thermal diffusivity can be estimated for every pixel in the PIT image, and analyzing the statistical distribution can reveal information about material state. Preliminary study validates algorithm performance for computer-simulated PIT data and experimental measurements with metallic and ceramic specimens.