GROZ, Marie-Marthe; SOMMIER, Alain; ABISSET, Emmanuelle; CHEVALIER, Stephane; BATTAGLIA, Jean-Luc; BATSALE, Jean-Christophe; PRADERE, Christophe

doi:10.1080/17686733.2020.1771529

SOMMIER, Alain
Institut de Mécanique et d'Ingénierie [I2M]

ABISSET, Emmanuelle

Institut de Mécanique et d'Ingénierie [I2M]

Langue

Article de revue

Ce document a été publié dans

Quantitative InfraRed Thermography Journal. 2020

Taylor and Francis

Date de soutenance

2020

Résumé en anglais

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 50,000 pixels by 4000 time steps with a reasonable relative error of less than 5%.< Réduire

Mots clés en anglais

InfraRed Thermography

Inverse Processing

Quantitative Thermal Resistance Fields Estimation

Bayesian Inference

URI

https://oskar-bordeaux.fr/handle/20.500.12278/75947

DOI

http://dx.doi.org/10.1080/17686733.2020.1771529

Origine

Importé de hal

Unités de recherche

Institut de Mécanique et d’Ingénierie de Bordeaux (I2M) - UMR 5295

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Thermal resistance field estimations from IR thermography using multiscale Bayesian inference