Monitoring of thermal degraded AC machine winding insulation by inverter pulse excitation
Bibliographic record
Abstract
The demand for AC machines in traction applications fed by voltage source inverters is increasing. These highly efficient drives working near and even above their rated values are expected to operate for many years or even decades. Thus, condition monitoring is gaining a more important role. With focus in this work on outages due to deteriorated machine winding insulation an online monitoring method is presented to detect changes in the insulation strength. With the proposed method the insulation system state is assessed before an actual short circuit occurs, without the need for additional equipment or disconnection of the drive. The inverter is used as a source of excitation, by applying pulse sequences with different duration to enable high frequency excitation and analysis in a range suitable for the insulation condition monitoring. The evaluation of a change in the electrical strength of the insulation is made by analyzing the transient current responses measured with the built-in sensors of the inverter.
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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".