TERRAIN 3D - TERmographic Reconstruction At INner 3D Interfaces

• Applicant: Professor Dr. Marc Daniel Leonhard von Kreutzbruck
• Subject Area: Measurement Systems ; Production Systems, Operations Management, Quality Management and Factory Planning
• Term: since 2021
• Project identifier: Deutsche Forschungsgemeinschaft (DFG) - Project number 470535306

In non-destructive testing, active thermography has established itself as a non-contact and comparatively inexpensive measurement and testing method in science and industry. A test specimen is typically irradiated with infrared radiation from an external energy source, which accumulates at defects and is reflected. The defects can be made visible by recording them with an infrared camera. A well-established method of active thermography is lock-in thermography with sinusoidal energy input. This makes it possible to inspect flat, thin components quickly and close to the surface. In the previous project, lockin thermography was extended to include a compensation algorithm that can iteratively compensate for lateral heat flows. Lateral heat flows cause thermal energy to spread laterally in the test specimen, resulting in blurred or distorted images of defects and making precise localization or depth determination more difficult. With homogeneous and isotropic materials, the lateral heat flows can be successfully compensated for with the developed compensation method and interfering blind frequencies can be eliminated. This is to be continued in the planned project and applied to complex, realistic materials. In this context, the algorithm will initially be extended to edge areas of test specimens (deviations from a plate-like shape). The compensation algorithm will then be applied and extended to complex materials. In this context, heterogeneous, anisotropic and heterogeneous-anisotropic test specimens are examined. This requires excitation with a sufficiently high power, which is why a flexible infrared emitter is to be expanded with an increase in power. In this way, a sufficient compensation effect can also be achieved with heterogeneous and anisotropic materials, where a higher lateral heat dissipation is to be expected. It will also be investigated whether and to what extent the compensation effect can be improved by incorporating material knowledge. In this context, neural networks are also to be used and artificial intelligence trained. The work to be carried out will be simulative and experimental.

• DFG Programme: Research Grants