Locked-rotor and acceleration testing of large induction machines-methods, problems, and interpretation of the results
Bibliographic record
Abstract
The measurement of locked-rotor current, torque, and power factor has been a standard test for induction machines for many years. Measurement of torque has evolved from using a brake, a dynamometer, a torque arm, and scale, through strain gauges and load cells to acceleration tests. The test must be of short duration to prevent damage to the machine and large machines present problems because of facility limitations in either kilovoltampere or torque measurement. A single test at reduced voltage when prorated to operating voltage by the square of the ratio of rated voltage to test voltage neglects the impact of saturation and results in significantly lower values of predicted torque and current. This paper discusses several methods for performing the locked-rotor and the speed-torque tests on large machines. It also discusses some of the problems associated with the test methods and shows how the tests can be performed and the results evaluated to account for saturation effects. Finally, the paper shows how to extract some machine circuit parameters from the test data.
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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 | 0.003 | 0.013 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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".