RITA - Robotized Inspection by Thermography and Advanced processing for the inspection of aeronautical components
Bibliographic record
Abstract
Active thermography is often performed on a static configuration where all elements of the thermographic system, i.e. the infrared camera, the energy source and the inspected object, are standing still with respect to each other.This is very useful for the application of signal processing techniques in order to improve defect detection and characterisation.Under this configuration, the large surfaces typical of some aeronautical components, are inspected in a series of static tests that at the end are assembled together on a single reconstructed mosaic image comprising the results for the entire inspected area.However, with the fast development of innovative and ever more complex-shaped parts, the alternative dynamic active thermography configuration is gaining attention.In this case, the component of interest is inspected in motion and the acquired data can be reorganized as a pseudo-static sequence, similar to classic static data, in order to perform advanced signal processing, if required.In this work, line scan thermography inspection was investigated for the assessment of an aerospace reference panel in the framework of the Canadian-Belgian collaborative project RITA (Robotized Inspection by Thermography and Advanced processing).
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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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.003 | 0.001 |
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".