Analysis and Modeling of a Synchronous Machine with Structural Asymmetries
Bibliographic record
Abstract
Most of the online fault diagnostic results are adversely affected by the supply unbalance and the structural asymmetries of the machine. However, in practice, it is impossible to realize a perfectly symmetrical electric motor fed by a balanced supply. Hence, in this paper, the influence of supply unbalance on the performance of synchronous machine with constructional asymmetries has been discussed. In order to conduct a theoretical study, asymmetries in the stator winding and the field winding of the machine have been considered. The field current signature analysis of the machine model with aforementioned asymmetries, with balanced and unbalanced supply, has been presented. In order to validate the theoretical results, experimental results by analyzing the field current and the voltage induced in a rotor-mounted search-coil of a synchronous machine have also been presented. The results of such a study will be extremely useful in developing unambiguous fault diagnostic tools
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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".