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Thermal resistance field estimations from IR thermography using multiscale Bayesian inference
- Source :
- Quantitative InfraRed Thermography Journal, Quantitative InfraRed Thermography Journal, Taylor and Francis, In press, ⟨10.1080/17686733.2020.1771529⟩
- Publication Year :
- 2020
- Publisher :
- Informa UK Limited, 2020.
-
Abstract
- International audience; 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%.
- Subjects :
- 010302 applied physics
Resistive touchscreen
Materials science
Field (physics)
Infrared
Thermal resistance
InfraRed Thermography
02 engineering and technology
Inverse Processing
Quantitative Thermal Resistance Fields Estimation
021001 nanoscience & nanotechnology
Bayesian inference
01 natural sciences
[SPI.MAT]Engineering Sciences [physics]/Materials
Flash (photography)
0103 physical sciences
Thermography
Thermal
Bayesian Inference
[PHYS.PHYS.PHYS-INS-DET]Physics [physics]/Physics [physics]/Instrumentation and Detectors [physics.ins-det]
Electrical and Electronic Engineering
0210 nano-technology
Instrumentation
Remote sensing
Subjects
Details
- ISSN :
- 21167176 and 17686733
- Volume :
- 18
- Database :
- OpenAIRE
- Journal :
- Quantitative InfraRed Thermography Journal
- Accession number :
- edsair.doi.dedup.....391cd4c9b6d3f71bf9389ae7abb78251