Experimental Investigation of the Spatial and Temporal Evolution of the Tangential and Normal E-Field Components along the Stress Grading System of a Real Stator Bar
Bibliographic record
Abstract
This paper presents results based on direct experimental measurements of tangential (Et) and normal (En) E-field components along the stress grading system (SGS) of a real stator bar (Roebel type) for different AC 60 Hz applied voltages. These measurements were made with a new electro-optic system allowing for the study of both spatial distributions of two E-field components along the bar and their temporal evolution at critical points. The results obtained allowed us to calculate the correlation between the distribution of En and Et along the SGS. In particular, it was demonstrated that the En distribution presents a characteristic minimum, which can be used to identify the zone of partial discharge inception. Moreover, it was possible to observe an enlargement of the Et component distribution followed by a saturation in magnitude with the applied voltage increase. Moreover, the results have demonstrated that the waveform of the En component is mostly affected by the SG material used, producing a greater distortion in its waveform than those obtained for the Et component. The more significant distortion was obtained at the end of the outer corona protection (OCP) material, corresponding to the first maximum of the En component and characterized by the appearance of a third harmonic of large amplitude.
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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 | 0.001 |
| 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".