Revolving-field polygon technique for performance prediction of single-phase induction motors
Bibliographic record
Abstract
This paper presents a new analytical technique for improving the performance prediction of single-phase induction motors, especially capacitor motors. The technique uses the split-phase motor electrical equivalent circuit analysis together with electrical and magnetic parameters whose variation is computed from the equivalent balanced polyphase motor, so that the same magnetic circuit analysis can be used for both. The technique accounts for the elliptical envelope of the magnetizing field vector and results in improved precision, since the three-phase electromagnetic model is considered to be more precise than the normal split-phase motor analysis. An important result is the computation of vector polygons of flux-density for each section of the magnetic circuit, providing a better basis for core loss prediction. The double-frequency torque ripple is also obtained from the stator MMF and flux-density polygons. Three different electrical equivalent circuit methods for the split-phase motor (based respectively on the cross-field theory, forward-and-backward revolving fields, and symmetrical components) are evaluated to determine the method best suited for incorporating the variation of the circuit parameters from the polyphase magnetic circuit analysis, and it is discussed how the core losses can be included in these circuits to obtain the best overall performance prediction.
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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 | 0.000 |
| 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) | 0.000 | 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".