Calibration of multi-axis MEMS force sensors using the shape from motion method
Bibliographic record
Abstract
This paper presents a new design of a two-axis MEMS (microelectromechanical systems) capacitive force sensor with strict linearity and a new sensor calibration method for micro-sensors. Precise calibration of multi-axis micro force sensors is difficult for several reasons, including the need to apply many known force vectors at precise orientations at the micro force scale, and the risk of damaging the small, fragile MEMS device. In this paper the shape from motion method is introduced for micro force sensors resulting in a rapid and effective calibration technique. Structural-electrostatic coupled field simulations are conducted in order to optimize the sensor design, which is calibrated with the shape from motion method as well as the least squares method for comparison purposes. Calibration results demonstrate that the shape from motion method is an effective, practical, and accurate method for calibrating multiaxis micro force sensors
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How this classification was reachedexpand
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 | 0.000 | 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 itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, 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".