Root crack sizing using phased array inspections and autoregressive spectral extrapolation signal processing
Bibliographic record
Abstract
Phased array inspection was conducted on a V-butt welded steel sample with multiple shallow flaws of varying depths. The inspection measurements were processed using Wiener filtering and Autoregressive Spectral Extrapolation (AS) to enhance the signals. Phased array inspections were conducted using multiple phased array probes of varying nominal central frequencies (2.25, 4, 5 and 10 MHz). This paper describes the measured results, which show high accuracy, typically in the range of 0.1-0.2 mm. The results concluded that: 1. There was no statistical difference between the calculated flaw depths from phased array inspections at different flaw tip angles. 2. There was no statistical difference in flaw depths calculated using phased array data collected from either side of the weld. 3. Flaws with depths less than the estimated probe signal shear wavelength could not be sized. 4. Finally, there was no statistical difference in the calculated flaw depths using phased array probes with different sampling frequencies and destructive measurements of the flaws.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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".