Novel technique to evaluate the erosion resistance of silicone rubber composites for high voltage outdoor insulation using infrared laser erosion
Bibliographic record
Abstract
The standard methods available to test tracking and erosion resistance of filled silicone rubber do not allow to delineate the fundamentals of the thermal degradation, although the heat from the dry band arcing is the main degradation factor. In this work a thermal imaging camera is used to investigate the performance of filled silicone rubber in an inclined plane test, and a scheme is established to relate the temperature and the electrical discharge energy. Further, an infrared laser technique, based on constant energy approach, is developed to study the material performance under laser heating. The technique consists of applying a certain amount of infrared laser energy during a set time period, in order to produce erosion in the silicone rubber samples. Through correlation studies the applicability of the proposed laser technique to rank silicone rubber samples with various fillers has been validated. The laser tests show identical ranking of samples when compared to samples ranked using inclined plane tests, yet offering significant advantages of being faster, simpler, and reproducible.
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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 | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| 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".