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Record W3039042326 · doi:10.1115/1.4047720

Design and Configuration of Folded Platonic Strapdowns of Biaxial MEMS Accelerometers

2020· article· en· W3039042326 on OpenAlexafffund
Xiaowei Shan, Jorge Angeles, James Richard Forbes

Bibliographic record

VenueJournal of Mechanical Design · 2020
Typearticle
Languageen
FieldEngineering
TopicAdvanced MEMS and NEMS Technologies
Canadian institutionsMcGill University
FundersNatural Sciences and Engineering Research Council of CanadaFaculty of Engineering, McGill University
KeywordsAccelerometerInertial measurement unitMicroelectromechanical systemsGyroscopeMiniaturizationAccelerationRotary encoderEncoderEngineeringComputer scienceAcousticsPhysicsAerospace engineeringElectrical engineering

Abstract

fetched live from OpenAlex

Abstract The authors report on the design, configure, and test of isotropic accelerometer strapdowns for high-precision inertial measurement unit (IMU) and folded MEMS configuration. The biaxial low-g MEMS accelerometers are based on the Platonic solids. A Platonic strapdown is integrated into an embedded system for acceleration-array signal acquisition targeting rigid-body pose-and-twist estimation. The electromechanical properties for dynamic sensitivity are tested on a haptic manipulator, which shows that the position estimation matches reasonably well the encoder readouts. The Platonic strapdown is promising in folded MEMS IMU with chip-level miniaturization and high estimation precision.

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 distilled prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation 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 score0.775
Threshold uncertainty score0.382

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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 head0.058
GPT teacher head0.243
Teacher spread0.185 · 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 teacher head, 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

Citations0
Published2020
Admission routes2
Has abstractyes

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