Fast Detection of Power Transistor Faults in SRM Drives Based on Transient Pulse Injection
Bibliographic record
Abstract
Switched reluctance motors (SRMs) have been widely used in reliability-critical applications due to their robust rotor structure and fault-tolerance characteristics. However, power transistors in the SRM drives still suffer from various faults, such as open-circuit and short-circuit faults, which may cause unexpected shutdowns. Therefore, detection and localization of the power transistor faults in the earliest stage is of extreme importance to ensure uninterrupted operations. This article proposes a fast fault diagnostic technique for power transistor faults in the SRM drive system. When a fault-caused abnormal current pattern is observed in the fundamental current, two complementary high-frequency (HF) pulses are injected into both power switches of the affected phase for a transient period. Through analyzing the relationship between the induced phase currents due to the injected HF pulses and the failure cases, two fault variables are introduced for faulty switch localization. Diagnosis of open-circuit and short-circuit faults in a single switch and dual switches is achieved within one period of the injected HF pulses. The fast diagnostic speed and feasibility of the proposed method for real-time implementation is verified through simulation studies and experiments based on a three-phase 12/8-pole SRM drive system.
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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 | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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".