Study on the Effect of Dynamic Eccentricity on Acoustic Noise of an Interior Permanent Magnet Traction Motor
Bibliographic record
Abstract
The modeling of acoustic noise is an important step in the design of traction motors for noise-sensitive applications. Eccentricity, which is a common type of manufacturing imperfection, can be a source of acoustic noise in traction motors. This paper presents a comprehensive analysis of the effect of dynamic eccentricity on the acoustic noise in a 48/8 interior permanent magnet traction motor. After considering the dynamic eccentricity, the extra dominant radial force harmonics are identified. The acoustic noise simulation is conducted based on a fast-numerical method, which can significantly reduce the computation cost without sacrificing the accuracy. The effect of dynamic eccentricity on the acoustic noise performance of the motor is discussed. Results show that a higher Sound Pressure Level (SPL) appears in a wider speed range when dynamic eccentricity is considered.
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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".