Applications of ultrasonic NDE techniques for location and characterization of defects in epoxy composite GIS spacers
Bibliographic record
Abstract
Ultrasonic inspection of gas-insulated high-voltage substation (GIS) spacers has been conducted and, based on the limited evaluation to date, it appears to provide a viable means of detecting defects. Using commercially available ultrasonic equipment coupled to a motor drive and software data collection system, this method has been successful in locating voids, agglomerates of contaminating particles, and epoxy-metal interface debonding in GIS spacers that failed to pass factory qualification tests. Manual probe application has also proven capable of locating defects. A series of defects including voids, metal contaminants, and paper fragments could be detected in a set of test specimens. A spatial resolution of approximately 1 mm has been attained. The correlation between ultrasonic results and forensic examination has been very good. The spacers used in this evaluation had previously been subjected to nondestructive X-ray tomographic inspection, which failed to disclose any internal defects. Scattering of the ultrasonic signal by the inorganic fillers has resulted in enlargement of the apparent dimensions of features. The fillers have not hindered detection of features within epoxy sections approximately 180 mm thick.>
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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".