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Séminaires REPARTI


Les Séminaires REPARTI à l'Université Laval ont lieu le vendredi à 11h30.
Veuillez consulter le programme pour plus de détails.

Projet de maîtrise, de doctorat ou stage postdoctoral en apprentissage automatique au sein de l'équipe du Prof. Christian Gagné : veuillez consulter l'annonce suivante pour tous les détails : http://vision.gel.ulaval.ca/~cgagne/postes2017.html

 

 

 

 

REPARTI

MIVIM

Dec 9 2016 11:30AM

Frank Billy Djupkep Dizeu
Laboratoire LVSN
Dép. de génie électrique et de génie informatique, Université Laval


Three-dimensional quantitative nondestructive testing of objects of complex shape using infrared thermography



Résumé

On the basis of its thermal behaviour, the state of an object can be evaluated, without damages and without contact, using infrared thermography. The result of the nondestructive evaluation of an object can be qualitative (location of areas with defects) or quantitative (determination of the defects' depth and size). Quantitative nondestructive testing (QNDT) using infrared thermography (IRT) can be viewed as an inverse geometry problem which consists in reconstructing the internal geometry and the rear surface of the inspected object using the temperature history measured on its frontal surface. We present a method for QNDT of objects of complex shape using IRT. The final objective is to be able to reconstruct the rear surface of such objects whatever their geometry. For that three steps are involved. We first propose a three-dimensional model for NDT using IRT and we develop a 3D meshless solver which has many advantages (computing time, adaptability to complex domains, ease of coding and implementation) compared to mesh-based solvers. The second step consists in determining the heat flux density resulting from the external thermal stimulus on the frontal surface. This spatiotemporal heat flux density is determined using only the temperature measured on the frontal surface by an infrared camera and the 3D point cloud of the frontal surface collected by a 3D scanner. The third step is the reconstruction of the rear surface of the inspected object. This is possible by solving an inverse geometry problem after a suitable parametrization of the unknown surface.


Note: Le séminaire sera présenté à 11h30 à la salle PLT-1120.




     
   
   

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