Uncertainty Propagation for Ring-Based Vibratory MEMS Gyroscopes Under Random Input Angular Speed Fluctuation
Bibliographic record
Abstract
Uncertainty quantification for ring-type MEMS gyroscopes due to frequency mismatch as well as quality factor is investigated. A suitable two-degree of freedom dynamic model is used to represent the vibratory behavior of a ring-gyroscope considering the second flexural modes. For the purposes of characterizing the vibratory behavior due to uncertain system as well as environmental parameters, steady state portion of transient responses are considered. Monte Carlo simulation method is used for estimating the ensemble mean as well as the standard deviation (measure of variance) of response samples. Employing an optimal sample number predicted via simulations, uncertainty quantification for the response statistics are evaluated via ensemble mean and standard deviations. It is envisaged that the predictions made from the output response statistics and uncertainty quantification analyses of the present study can lead to significant performance improvements in the design of this class of micro-machined ring-type vibratory angular rate sensors.
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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 | 0.003 | 0.010 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| 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 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".