Defect depth estimation using pulsed eddy current with varied pulse width excitation
Why this work is in the frame
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Bibliographic record
Abstract
Current industry requirements demand defect quantification rather than simple defect detection. Besides the defect geometrical size, its depth location plays a critical role for the integrity of a structure and the safe life operation of the overall assembly. It has been long known that pulsed eddy current (PEC) non-destructive testing (NDT) for electrically conductive materials has the advantage of gathering different depth information in a single excitation process. This fact is due to the low frequencies found in the pulse spectrum that is used for the excitation of the driving coil; however, quantifying the defect depth still remains a challenge. This study considers different pulse widths and frequency components as a method of defect depth discrimination with direct applications in the evaluation of corrosion defects in multi-layer aircraft structures. Experimental testing and numerical modelling approaches are concomitantly discussed as ways of defect depth quantification.
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Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 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 it