17 Septembre – Thesis defense - Marie-Marthe Groz
14 h Amphi LaBRI / Building A30 (Talence campus)
3D reconstruction of volumetric heat sources from surface temperature fields measured by infrared thermography.
Non Destructive Testing (N.D.T.) of materials and structures is a very important industrial issue in the fields of transport, aeronautics and space and in the medical domain. Active infrared thermography is a N.D.T. method that consists in providing an external excitation to cause an elevation of temperature field in the material and then to evaluate the resulting temperature field at the surface. However, thermal exciters used (flash lamps, halogen, lasers) act only on the surface of the sample. Several energy conversion systems can on the other hand lead to the generation of volumetric sources: the phenomena of thermo-acoustic, thermo-induction, thermomechanic or thermochemistry can be cited. For example, ultrasonic waves can generate volumetric heat sources if the material is viscoelastic or if there is a defect. The reconstruction of these sources is the first step for the quantification of parameters responsible of the heating. Characterizing a heat source means reconstructing its geometry and the power it generates. For example, a defect in a structure and / or the viscoelasticity of a material can be detected and quantified by this technique if it acts directly on temperature field. However, identification of volumetric heat sources from surface temperature fields is a mathematical ill-posed problem. The diffusive nature of the temperature is the main cause. In this work, the 3D reconstruction of the volumetric heat sources from the resulting surface temperature field, measured by InfraRed, is studied. First, an analysis of the physical problem enables to specify the limits of the reconstruction. In particular, a criterion on achievable spatial resolution is defined and a reconstruction limitation for in-depth sources is highlighted. Then, a probabilistic approach for the reconstruction is proposed and compared to existing inverse methods. The computation time and noise sensitivity are studied for each of these methods. Numerical and experimental applications will thus be presented to illustrate the results.