On-line monitoring for condition assessment of motor and generator stator windings
Bibliographic record
Abstract
Deterioration of the stator windings continues to be one of the predominant causes of large motor and generator failures. Over the past several years, much research has been done to develop technologies to provide plant maintenance personnel with better, more objective methods of assessing the condition of machine windings. Through this work, practical methods have been developed for measuring the partial discharge activity in the high voltage insulation of stator windings, since partial discharges are a symptom of most of the major insulation failure mechanisms. One test, called the PDA test, has been successfully used by utilities for many years, and can be performed by plant maintenance personnel during normal operation of a hydrogenerator. A similar partial discharge test, called the TGA test, has now been specifically developed for turbine generators and high voltage motors and is described in this paper. The TGA test allows motor and generator users of machines rated 4 kV and above, to reliably perform an in-service partial discharge test and through interpretation of the test results to confidently assess stator winding condition and plan machine maintenance requirements. Since the test is done by plant personnel during normal motor or generator operation, testing costs are also very low.>
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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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.006 | 0.002 |
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".