Design of a VCM Actuator Using Halbach Magnet Array for Active Vibration Isolation System
Bibliographic record
Abstract
This paper proposes the concept development and design of a VCM actuator for Active Vibration Isolation System (AVIS). Active vibration isolating method was constructed passive isolator and active isolator. Spring was used for isolating passively and actuator like voice coil motor was used for active isolating. The proposed active vibration isolating system could isolate a six degree-of-freedom disturbance effectively. In case of AVIS, payload is variable according to the type of instruments. Therefore, actuator should maintain uniform performance with payload change. The proposed VCM actuator satisfied this performance through relative relation between magnet array and coils. In addition, for maximizing actuator performance, actuator should generate large force density. Therefore, we apply the Halbach magnet array to proposed actuator. The Halbach magnet array helps with reinforcing magnetic flux field. The reinforced magnetic field takes a role to generate more powerful Lorentz force to isolate disturbance. Finally, in this paper, we propose the actuator that novel type using voice coil motor with the Halbach magnet array and optimize each design variables to generate maximum output. These AVIS can use to eliminate disturbance in Maglev stage. Maglev stage need AVIS to increase its performance is necessary. In the future, AVIS and Maglev system will be integrated.
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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 | 0.001 | 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".