Experience with high potential testing hydro generator multi turn stator coils using 60 Hz AC, DC, and VLF (0.1 Hz)
Bibliographic record
Abstract
There are many different methods of employing a high potential test on a stator winding. Three such methods that this paper will explore with reference to one another are the AC (50-60 Hz), DC, and very low frequency (VLF) (0.1 Hz). Some users choose the AC high potential test knowing that this test best simulates the voltage stress on the winding while in service. Other users prefer the DC high potential test largely due to ease in performing the test. However, the DC voltage does not stress the stator coils the same way as when they are in service and may result in overly pessimistic results due to the influence of surface contaminants in the end windings. Finally, the VLF test, due to recent advances in technology, is becoming more practical for use in field conditions. However, the present standard governing the test is almost 40 years old and there is significant interest in what VLF voltage level best correlates with the AC and DC high potential tests. This paper reports preliminary test results on three generator windings that were destructively tested using the AC, DC, and VLF methods as part of an ongoing effort to provide a database upon which to set the appropriate VLF hipot level for modern synthetic resin-based stator insulation systems.
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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 | 0.006 | 0.008 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.002 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 0.001 |
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".