Survivability-Based Protection for Electric Motor Drive Systems-Part I: $3\phi$ Induction Motor Drives
Bibliographic record
Abstract
This article develops a survivability-based protection for three-phase induction motor drive ($3\phi$IMDs) systems against severe dynamic events. The developed protection is based on defining a survivability index$\Gamma _{\text{IMD}}$, which is formulated in terms of the change in power created by a dynamic event experienced by a$3\phi$IMD. The determination of$\Gamma _{\text{IMD}}$provides an accurate tool to detect, identify, and respond to unsurvivable dynamic events. The efficacy and validity of the survivability-based protection for$3\phi$IMDs are verified through simulation and experimental tests. These tests are conducted for 10 hp$3\phi$IMD under various types of dynamic events. Test results demonstrate the effectiveness of the survivability-based protection in responding to unsurvivable dynamic events to prevent damage to different components in a$3\phi$IMD.
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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 | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 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".