Low frequency ultrasound NDT of power cable insulation
Bibliographic record
Abstract
Ultrasound technology is a very well-known effective technique used in Non-Destructive Testing (NDT). Of the advantages, one can name its relatively low cost and that it is safe. At high frequencies it offers the capability of generating high resolution imagery. Unfortunately at high frequencies ultrasound waves are highly attenuated in air and within materials attenuation also worsens as the frequency increases. Additionally, transmission in air results on a considerable impedance mismatch between the propagating medium and the materials under inspection. Thus a coupling medium is used that limits its applications to materials that can be either immersed in water or be in touch with coupling gel. In this paper we explore the use of 25 KHz frequency transducers used in air with no coupling material. We trade the benefits of high resolution imaging for effective fault detection with a system that offers its own benefits. By choosing such a low frequency we alleviate in part the attenuation of high frequency sound waves within the material and air but by not using a coupling medium the transmitted power to the sample is highly attenuated. Our main application, detection of faults within the insulation material of power cables requires such a system. We report that detection is possible.
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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) | 0.002 | 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".