A Formula for Class F Induction Motor Specified Temperature
Bibliographic record
Abstract
In this paper, a formula to estimate the specified (full-load) temperature of insulation class F induction motors is proposed. The formula is structured via an extensive investigation conducted on a database which consists of 141 small- and medium-sized induction motors, in the range of 1-500 hp, provided by the Laboratoire des Technologies de l'Énergie, Institut de Recherche, Hydro-Québec. The same is done on another tests set of 46 (aged) induction motors of the same insulation class that is provided by BC Hydro. To validate the proposed formula, the stator I2R loss is calculated based on the corrected stator resistance as per the measured full-load temperature, IEEE assumed temperature, and the proposed temperature formula. A comparison is conducted using the absolute normalized percentage error resulted from both the IEEE and the proposed formula. The new formula demonstrates better accuracy. This formula shows the potential to replace the existing IEEE formula for Class F induction machines in the 1-500 horsepower range.
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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 | 0.011 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.003 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| 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 | 0.002 |
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".