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Photothermal image reconstruction in opaque media with virtual wave backpropagation

Gregor Thummerer, G. Mayr, Philipp Daniel Hirsch, Mathias Ziegler, Peter Burgholzer

2020NDT & E International20 citationsDOIOpen Access PDF

Abstract

Thermographic reconstruction of defects that lie in the bulk of a sample is a difficult task because entropy production during heat diffusion leads to information loss. To reconstruct defects one has to solve an inverse heat conduction problem. The quality of the reconstruction is closely related to the information content of the observed data set that is reflected by the decreasing ability to spatially resolve a defect with growing defect depth. In this work we show a 2D reconstruction of rectangular slots with different width-to-depth ratios in a metallic sample. For this purpose, we apply the virtual wave concept and incorporate positivity and sparsity as prior information to overcome the diffusion-based information loss partially. The reconstruction is based on simulated and experimental pulse thermography data. In the first reconstruction step, we compute a virtual wave field from the surface temperature data. This allows us, in the second step, to use ultrasonic backpropagation methods for image reconstruction.

Topics & Concepts

BackpropagationOpacityIterative reconstructionArtificial intelligenceInverse problemThermographyThermal conductionArtificial neural networkSurface reconstructionSample (material)Computer scienceComputer visionAcousticsMaterials scienceOpticsMathematicsSurface (topology)PhysicsGeometryThermodynamicsInfraredComposite materialMathematical analysisThermography and Photoacoustic TechniquesPhotoacoustic and Ultrasonic ImagingOptical measurement and interference techniques
Photothermal image reconstruction in opaque media with virtual wave backpropagation | Litcius