Abstract
We combine three different approaches to greatly enhance the defect reconstruction ability of active thermographic testing. As experimental approach, laser-based structured illumination is performed in a step-wise manner. As an intermediate signal processing step, the virtual wave concept is used in order to effectively convert the notoriously difficult to solve diffusion-based inverse problem into a somewhat milder wave-based inverse problem. As a final step, a compressed-sensing based optimization procedure is applied which efficiently solves the inverse problem by making advantage of the joint sparsity of multiple blind measurements. To evaluate our proposed processing technique, we investigate an additively manufactured stainless steel sample with eight internal defects. The concerted super resolution approach is compared to conventional thermographic reconstruction techniques and shows an at least four times better spatial resolution.
Original language | English |
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Article number | 9336334 |
Pages (from-to) | 7368-7378 |
Number of pages | 11 |
Journal | IEEE Transactions on Industrial Informatics |
Volume | 17 |
Issue number | 11 |
DOIs | |
Publication status | Published - Nov 2021 |
Keywords
- active thermography
- additively manufactured stainless steel
- ADMM
- block regularization
- internal defects
- joint sparsity
- laser excitation
- multi-dimensional reconstruction
- photothermal super resolution
- virtual waves
- Internal defects
- Photothermal super resolution
- Laser excitation
- Active thermography
- Alternating direction method of multipliers (ADMM)
- Additively manufactured stainless steel
- Joint sparsity
- Block regularization
- Multidimensional reconstruction