Analysis of a hydro-generator stator winding failure
Bibliographic record
Abstract
When a winding failure occurs in a hydro-generator, an investigation should first be organized to locate and assess the extent of the fault. A visual inspection and electrical tests are used to accomplish this task. The goal is not only to determine what must be repaired to return the generator to service as soon as possible, but also to find the root cause of the failure and collect valuable data for use in winding insulation condition assessment. These two aspects of failure analysis provide important information that complements the information obtained during periodic generator inspections. This paper presents a case study of winding failure on a 51 MVA, 11 kV generator stator. It describes the stator condition assessment carried out to determine the root cause of the failure and obtain additional information on the winding condition assessment, as well as the findings of the visual inspection and details of the dissection and measurement campaign performed prior to returning the repaired generator to service.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| 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 | 0.001 |
| 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 teacher head, 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".