Guided Lamb waves and L-SAFT processing technique for enhanced detection and imaging of corrosion defects in plates with small depth-to wavelength ratio
Bibliographic record
Abstract
The Lamb synthetic aperture focusing technique (L-SAFT) imaging algorithm in the Fourier domain is used to produce Lamb wave imaging in plates while considering the wave dispersive properties. This artificial focusing technique produces easy-to-interpret, modified B-scan type images of Lamb wave inspection results. The high level of sensitivity of Lamb waves combined with the L-SAFT algorithm allows one to detect and to produce images of corrosion defects with small depth-to-wavelength ratio. This paper briefly presents the formulated L-SAFT algorithm used for Lamb waves and, in more details, some experimental results obtained on simulated and real corrosion pits, demonstrating the benefit of combining L-SAFT with pulse-echo Lamb wave inspection. The obtained images of the real corrosion defects showed detection of pits with a depth-to-wavelength ratio of approximately 2/11.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".