Mechanical Fault Detection in a Medium-Sized Induction Motor Using Stator Current Monitoring
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Bibliographic record
Abstract
This paper presents the results of an experimental study of the detection of mechanical faults in an induction motor. As is reasonably well known, by means of analysis of combinations of permeance and magneto-motive force (MMF) harmonics, it is possible to predict the frequency of air gap flux density harmonics which occur as a result of certain irregularities in an induction motor. In turn, analysis of flux density harmonics allows the prediction of induced voltages and currents in the stator windings. Reviewing this theory, equations which may aid in the identification of mechanical faults are presented. These equations include both those which indicate eccentric conditions and those which have been suggested to help identify bearing faults. The development of test facility to create eccentricity faults and bearing fault conditions is described. This test facility allows rapid access to the motor bearings, allowing an investigation into the ability to detect faulted bearing conditions using stator current monitoring. Experimental test results are presented, indicating that it may be possible to detect bearing degradation using relatively simple and inexpensive equipment.
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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 | 0.000 |
| 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 it