UHF Detection of the Eroding DC Dry-Band Arcing on Silicone Rubber Insulation
Bibliographic record
Abstract
This article proposes ultra-high frequency (UHF) detection of the eroding dry-band arcing as a non-intrusive and online detection technique of erosion failure during the dc inclined plane test (IPT). Tests are performed on silicone rubber (SR) composites, while conducting leakage current (LC), surface temperature, and UHF measurements using a horn antenna. No UHF detection is evident during mild dry-band arcing (DBA), which does not lead to erosion. Whereas, the detection is evident during stable DBA, particularly when the intensity becomes remarkable. Thermogravimetry, differential thermal analysis, and Fourier Transform spectroscopy are conducted to elucidate temperature measurements and visual observations. The eroding DBA is shown to lead to depolymerization of SR at$400~^{\circ }$C, thereby leading to combustion and erosion failure, and stimulating a radical-based crosslinking reaction at temperatures exceeding$500~^{\circ }$C. The intensity of the UHF detection is also shown to be sensitive to the severity of the eroding DBA as it increases with time during the test or with higher applied test voltages.
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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 | 0.000 |
| 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) | 0.001 | 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".