Torque-Ripple-Based Interior Permanent-Magnet Synchronous Machine Rotor Demagnetization Fault Detection and Current Regulation
Why this work is in the frame
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Bibliographic record
Abstract
To develop a reliable permanent-magnet synchronous machine (PMSM) controller for electric vehicle application, detection of permanent-magnet (PM) demagnetization conditions is of significance. This paper explores the use of torque ripple for online PM demagnetization fault diagnosis using continuous wavelet transforms (CWT) and grey system theory (GST). First, a torque-ripple-based rotor flux linkage detection model considering electromagnetic noises is proposed, which employs CWT filtering, wavelet ridge spectrum, and torque ripple energy extraction. This model is able to reveal the torque variation and eliminate the effect of electromagnetic interferences. Second, GST is employed to facilitate the detection of demagnetization ratios and torque ripple energy pulsations caused by demagnetization. Third, a current regulation strategy is proposed to minimize the torque ripples induced by PM demagnetization, which contributes to making the approach feasible to interior PMSM (IPMSM). Furthermore, the proposed real-time irreversible demagnetization detection approach can identify the demagnetization fault under different operating conditions. The proposed approach and current regulation strategy are experimentally verified on a down-scaled laboratory IPMSM.
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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 it