Emulation of an Induction Machine with Inclined Eccentricity fault
Bibliographic record
Abstract
Rising recognition of the financial risks posed by sudden failures in electric machines, particularly those operating under critical conditions, underscores the need for advanced fault diagnosis. Among the various mechanical faults, eccentricity faults, especially inclined or axially non-uniform static eccentricity, remain less explored in the literature despite their practical relevance. This paper develops a mathematical model based on the modified winding function method (MWFM) for a wound rotor induction motor to address this gap. Furthermore, it explores the application of power hardware-in-the-loop (PHIL) based emulation techniques to accelerate the testing of these eccentricity faults. Experimental data validate the mathematical model and underscore the efficacy of the PHIL-based machine emulator in emulating different degrees of eccentricity fault conditions. Additionally, the study contrasts the impacts of axially uniform and non-uniform static eccentricity, providing valuable insights into the detection of these faults.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| 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 source (direct Gemma or distilled Codex), 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".