Thermal resistance field estimations from IR thermography using multiscale Bayesian inference

Abstract

The main goal of this paper is the estimation of thermal resistive fields in multilayer samples using the classical front face flash method as excitation and InfRared Thermography (IRT) as a monitoring sensor. The complete inverse processing of a multilayer analytical model can be difficult due to a lack of sensitivity to certain parameters (layer thickness, depth of thermal resistance, etc.) or processing time. For these reasons, our present strategy proposes a Bayesian inference approach. Using the analytical quadrupole method, a reference model can be calculated for a set of parameters. Then, the Bayesian probabilistic method is used to determine the maximum likelihood probability between the measured data and the reference model. To keep the processing method robust and fast, an automatic selection of the calculation range is proposed. Finally, in the case of a bilayer sample, both the thickness and resistive 3D layers are estimated in less than 2 min for a space and time matrix of 50000 pixels by 4000 time steps with a reasonable relative error of less than 5%.

Thermographic Imaging in Cultural Heritage: A Short Review

“…Although passive thermography has been applied as a standard quality control technique for a long time, the thermographic inspection during and after a heating process has been proven to increase the potentiality in the absence of natural thermal contrasts [ 71 , 72 , 73 ]. Variations in the thermal properties in defective multilayer materials produce thermal effects, which are easily observable via active thermography (i.e., after the application of heat flows into the material bulk) [ 74 , 75 ]. A user-friendly procedure based on an active approach, targeting a long-term and sustainable approach for preserving ancient mosaic heritage was proposed by Theodorakeas et al [ 76 , 77 ].…”

Application of the Conjugate Gradient Method for Predicting Unknown Heat Flux in 2D Plat under Effect of Insulation

“…Gaverina et al, [35] analyzed the thermal diffusivity in the in-plane direction. Groz et al, [36] used an inverse method based on thermographic data to estimate the thermal resistance and layer thickness. Halloua et al, [37] proposed a fast and novel method that allows to estimate the thermal and physical properties of CFRP laminated composites.…”