Probability of detection for bolt hole eddy current in extracted from service aircraft wing structures
Bibliographic record
Abstract
Fatigue cracks are prone to develop around fasteners found in multi-layer aluminum structures on aging aircraft. Bolt hole eddy current (BHEC) is used for detection of cracks from within bolt holes after fastener removal. In support of qualification towards a target a90/95 (detect 90% of cracks of depth a, 95% of the time) of 0.76 mm (0.030”), a preliminary probability of detection (POD) study was performed to identify those parameters whose variation may keep a bolt hole inspection from attaining its goal. Parameters that were examined included variability in lift-off due to probe type, out-of-round holes, holes with diameters too large to permit surface-contact of the probe and mechanical damage to the holes, including burrs. The study examined the POD for BHEC of corner cracks in unfinished fastener holes extracted from service material. 68 EDM notches were introduced into two specimens of a horizontal stabilizer from a CC-130 Hercules aircraft. The fastener holes were inspected in the unfinished state, simulating potential inspection conditions, by 7 certified inspectors using a manual BHEC setup with an impedance plane display and also with one inspection conducted utilizing a BHEC automated C-Scan apparatus. While the standard detection limit of 1.27 mm (0.050”) was achieved, given the a90/95 of 0.97 mm (0.039”), the target 0.76 mm (0.030”) was not achieved. The work highlighted a number of areas where there was insufficient information to complete the qualification. Consequently, a number of recommendations were made. These included; development of a specification for minimum probe requirements; criteria for condition of the hole to be inspected, including out-of-roundness and presence of corrosion pits; statement of range of hole sizes; inspection frequency and data display for analysis.
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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 | 0.007 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 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".