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Record W2066274492 · doi:10.1115/imece2012-89394

Spurious Signals in the Thermal MEMS Gyroscope

2012· article· en· W2066274492 on OpenAlexafffund
Pooneh Shooshtari, Jamal Bahari, Kourosh Khosraviani, Albert M. Leung, John D. Jones

Bibliographic record

VenueVolume 9: Micro- and Nano-Systems Engineering and Packaging, Parts A and B · 2012
Typearticle
Languageen
FieldEngineering
TopicGeophysics and Sensor Technology
Canadian institutionsSimon Fraser University
FundersNatural Sciences and Engineering Research Council of Canada
KeywordsSpurious relationshipGyroscopeSIGNAL (programming language)AccelerationMicroelectromechanical systemsDistortion (music)ThermalRotation (mathematics)AcousticsVibrating structure gyroscopePhysicsElectronic engineeringEngineeringComputer scienceAerospace engineeringClassical mechanicsOptoelectronics

Abstract

fetched live from OpenAlex

The operational principle of a thermal MEMS (Micro Electro-Mechanical Systems) gyroscope was reported in Hilton Head 2010 [1]. In the current work we describe two factors that can produce a spurious rotation signal in gyroscopes of this type. These factors are, firstly, distortion or asymmetric placement of the heating elements or temperature sensors; secondly, the effects of linear acceleration and/or gravity on the fluid flow inside the device, and hence on the gyroscope output. In order to simulate the thermal gyro and the origin of these spurious signals, a mathematical model is built and developed through the COMSOL CFD package. The spurious signals predicted by this simulation are shown to correspond to experimental measurements. Alternative cavity shapes are investigated and simulated as a mean of suppressing the spurious signal.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame machine prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.007
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.001
Threshold uncertainty score0.005

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.007
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.000
Science and technology studies0.0000.001
Scholarly communication0.0010.001
Open science0.0010.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0010.000

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.

Opus teacher head0.006
GPT teacher head0.175
Teacher spread0.168 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designBench or experimental
Domainnot available
GenreEmpirical

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".

Quick stats

Citations6
Published2012
Admission routes2
Has abstractyes

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Same venueVolume 9: Micro- and Nano-Systems Engineering and Packaging, Parts A and BSame topicGeophysics and Sensor TechnologyFrench-language works237,207