Analysis and Enhanced Modeling of Inductive Displacement Sensor in Active Magnetic Bearing
Bibliographic record
Abstract
Inductive displacement sensors are commonly used in active magnetic bearing (AMB) applications. In most research, conventional models used to analyze inductive sensors in terms of determining sensitivity and obtaining a relationship between output voltage and displacement ignore the effects of fringing in air gaps. However, the effects of flux fringing on the performance of these sensors cannot be ignored in industrial applications. In this article, by using the Schwarz-Christoffel transformation, 3-D self-and mutual inductances for the radial and axial poles of a 3-degree-of-freedom inductive sensor are calculated, with the effects of fringing taken into account. The results of these calculations are compared with finite element results. The results show that the model based on the Schwarz-Christoffel method outperforms the ideal model in which flux fringing is ignored, with an inductance calculation error of about 8% for radial poles and 6.5% for axial poles, respectively.
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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 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| 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".