Demagnetization Fault Detection of Permanent Magnet Synchronous Motor Through Voltage Excitation at Standstill Condition
Bibliographic record
Abstract
Permanent magnet demagnetization (PMD) faults can result in reduced motor performance and reliability in the permanent magnet synchronous motor (PMSM) drive system. Existing PMD detection methods can be invasive or easily influenced by machine parameter variations, loading conditions, and other faults of the machine. This article introduces a noninvasive and computationally efficient approach to diagnose PMD faults of PMSMs at standstill which is independent of the machine operating conditions. In the proposed approach, a set of excitation voltages is designed and fed by the inverter to produce a current in the machine, thereby causing a magnetic flux variation in the PMSM at standstill. The PMD fault indicator is defined based on the corresponding current signal. More specifically, the phase currents are measured and processed to determine the PMD level by comparing with the healthy state current. In this article, it is also found that a position-dependent torque oscillation can be generated during the voltage excitation at standstill. Therefore, this article also addresses the torque oscillation issue under all different rotor positions. In addition, the permanent magnet (PM) flux linkage can be determined with the proposed approach. Extensive tests are conducted to validate the proposed approach in detecting PMD faults and determining the PM flux linkage experimentally and in simulations.
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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) | 0.001 | 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".