2020
DOI: 10.1038/s41598-020-77979-y
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Laser excited super resolution thermal imaging for nondestructive inspection of internal defects

Abstract: A photothermal super resolution technique is proposed for an improved inspection of internal defects. To evaluate the potential of the laser-based thermographic technique, an additively manufactured stainless steel specimen with closely spaced internal cavities is used. Four different experimental configurations in transmission, reflection, stepwise and continuous scanning are investigated. The applied image post-processing method is based on compressed sensing and makes use of the block sparsity from multiple… Show more

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Cited by 15 publications
(16 citation statements)
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“…For a regular measurement grid of equilateral triangles of side length r d = 0.743 mm across the ROI with n m = 403 vertices/independent measurement positions arranged in 7 rows with 54 or 53 positions each and subsequent reconstruction using the sparse matrix stacking approach, the resulting reconstruction of a rec is shown in Fig. (6). At each grid point a single measurement has been recorded after an illumination with a laser spot with spot size d spot = 0.6 mm at Q = 15 W. To eliminate the time dimension, an evaluation time of t eval = 500 ms has been taken into account.…”
Section: Resultsmentioning
confidence: 99%
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“…For a regular measurement grid of equilateral triangles of side length r d = 0.743 mm across the ROI with n m = 403 vertices/independent measurement positions arranged in 7 rows with 54 or 53 positions each and subsequent reconstruction using the sparse matrix stacking approach, the resulting reconstruction of a rec is shown in Fig. (6). At each grid point a single measurement has been recorded after an illumination with a laser spot with spot size d spot = 0.6 mm at Q = 15 W. To eliminate the time dimension, an evaluation time of t eval = 500 ms has been taken into account.…”
Section: Resultsmentioning
confidence: 99%
“…The reconstruction result for applying the sparse matrix stacking algorithm is shown in Fig. (6). For this reconstruction the ADMM-parameters λ 2,1 = 1570, λ 2 = 100, ρ = 16 and n iter = 400 have been used.…”
Section: Resultsmentioning
confidence: 99%
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