Bibliographic record
Abstract
A stator ground fault occurred in a hydrogen cooled synchronous condenser rated 300 MVA. This was as a result of a small metallic object that had been left in the rotor during an overhaul. The object had entered the air gap and damaged the end arms of three stator bars, one of which failed. The OEM patched the three stators bars. A series of off-line electrical tests were performed to assess the adequacy of the repair. One patch failed and had to be reapplied. There was concern about possible damage to the stator core and the field poles. A robotic inspection vehicle and camera were rented to examine all 132 teeth of the core over its 3.95 m length as well as the poles. Areas were observed and photographed where there was visual evidence of possible damage. The inspection vehicle was used to move the sensing coil of our digital EL CID along stator core teeth where there was the most evidence of damage. The information obtained indicated that the damage was not sufficient to warrant removing the rotor. This decision greatly reduced the duration and cost of the repair. Upon return to service on-line partial discharge measurements were made from directional bus couplers as well as from stator slot couplers with the machine operating in air and in hydrogen.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.004 | 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".