Demonstration of a Nonlinear Angular Rate Sensor based on Internal Resonance
Bibliographic record
Abstract
This paper reports on the design, fabrication and rate table characterization of an H-shaped tuning fork microresonator with 2:1 internal resonance as an actuation mechanism. The nonlinear principle of operation addresses major challenges in MEMS Coriolis vibratory gyroscopes: eliminating the mode-matching requirement, minimizing instability and drift due to mechanical cross-coupling between the fundamental modes, and generating a wide operating frequency range with high-signal gain and less sensitivity to fluctuations in driving frequency. The rate measurement relies on capturing the half-order subharmonic response of the device while undergoing the angular velocity. The micromachined resonator is fabricated using the MEMS Integrated Design for Inertial Sensors platform offered by Teledyne DALSA Inc. The experimental finding demonstrated the prominent M-shaped nonlinear resonant curves due to a frequency ratio close to 2:1. The microresonator is nominally operated in the overlap region between the forward and backward frequency sweeps, where the signal gain is less sensitive to frequency fluctuations. The microresonator described here operates at 561.23600kHz in a near 2:1 frequency ratio between two anti-phase resonant modes. Experimental rate characterization of the microresonator revealed a linear dynamic range of 220 deg sec-1with a sensitivity of 0.011 mV deg-1sec-1using an 80V DC polarization voltage. The experimental results of the microresonator showed the induced oscillations in the so-called pendulum mode by Coriolis force coupling, despite a clear disparity on natural frequencies of the desired modes.
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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 | 0.001 |
| 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 | 0.001 |
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".