Design and Validation of a Variable Reluctance Differential Solenoid Transducer
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
This paper presents a novel variable reluctance differential solenoid transducer (VRDST) that offers improved high-speed sensing performance over linear voltage differential transformers (LVDTs) and differential variable reluctance transformers (DVRTs). The VRDST has the unique ability to measure both position and velocity simultaneously using two independent measurements. This paper investigates a basic geometry for a VRDST. The position and velocity measurement methods are derived and implemented in a Simulink simulation. The simulated VRDST model is augmented with an FEA simulation to predict the magnetic characteristics of the investigated design. The results and predictions established by the simulation and analytical models are validated experimentally with a physical prototype. The similarity between the experimental and simulated results suggest the proposed FEA and Simulink simulations can be used to accurately predict the performance of a physical VRDST. The findings from the analytical modeling, simulation study and experimental validation all unanimously prove the position measurement performs well when measuring low-speed displacements, while the integrated-velocity measurement is useful for measuring high-speed displacements. The differing frequency ranges of these two independent measurements are found to complement each other and suggest the VRDST is superior compared to DVRTs or LVDTs for applications requiring wide bandwidth position measurements.
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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 | 0.001 | 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) | 0.000 | 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