The detection of broken bars in the cage rotor of an induction machine
Bibliographic record
Abstract
Techniques are described for the detection of broken bars in the cage rotor of an induction machine. A 30 hp, four pole induction machine with deep bar cage rotor was procured. A stator yoke, tooth tip, and external search coils and thermocouples were installed for test purposes. A shaft torque transducer was installed in line with a DC load machine. The cross section of the machine was modeled with finite elements, and the field distribution and mechanical performance were computed using a nonlinear, complex, steady-state technique. Broken bars were shown to produce high localized airgap fields and to degrade mechanical performance. The field perturbation associated with broken bars, deliberately disconnected from the endrings by machining, produces low-frequency components and harmonics in the search-coil-induced voltages, and gives rise to an oscillatory torque which produces noise and mechanical vibration. Experimental results show that analysis of the voltage induced in an external search coil is adequate to detect the presence of broken bars.>
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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 | 0.001 |
| 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 | 0.001 | 0.000 |
| Research integrity | 0.001 | 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".