Detection of Skin Disbond in Honeycombs and Coating Detachment by Laser Tapping Technique
Bibliographic record
Abstract
Many engineering structures are made of composite materials and include, for example, a protective coating or a bonded layer. We have developed a novel technique, similar to laser-ultrasonics that allows the detection of disbonds between the coating or the bonded layer and the substrate. The technique is also applicable to the detection of unbonds in honeycomb structures. The technique is based on the thermoelastic excitation by a laser pulse of the top layer or top skin which is driven into vibration if it is detached from the substrate underneath. This vibration is then detected by a second laser coupled to a photorefractive interferometer. This detection laser is a single frequency, very stable laser, which delivers optical pulses of a few hundred of microseconds, long enough to capture the low frequency membrane vibrations of the disbonded layers. Photorefractive interferometers allow processing these low frequencies while keeping the system insensitive to ambient vibrations. One of the most promising applications is the in-service inspection of aerospace structures for the detection of core unbonds in honeycombs or near surface delaminations. Keywords: Laser-ultrasonics, laser-ultrasound, laser-based ultrasound, disbonds, coatings, honeycomb structures.
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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 | 0.000 | 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".