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Record W2113860323 · doi:10.1109/robot.2007.363784

Simplectic Architectures for True Multi-axial Accelerometers: A Novel Application of Parallel Robots

2007· article· en· W2113860323 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.
fundA Canadian funder is recorded on the work.

Bibliographic record

VenueProceedings - IEEE International Conference on Robotics and Automation/Proceedings · 2007
Typearticle
Languageen
FieldEngineering
TopicRobotic Mechanisms and Dynamics
Canadian institutionsMcGill University
FundersNatural Sciences and Engineering Research Council of Canada
KeywordsAccelerometerAccelerationKinematicsProof massDisplacement (psychology)Computer scienceMicroelectromechanical systemsRigid bodyPiezoresistive effectAcousticsMaterials scienceEngineeringPhysicsElectrical engineeringNanotechnology

Abstract

fetched live from OpenAlex

Several triaxial accelerometers are known. However, to the knowledge of the authors, no true, triaxial accelerometers are commercially available. By true we mean an accelerometer which would pick up the three components of point-accelerations using one single proof-mass. What we propose is novel architecture classes of parallel-kinematics-machine for multi-axial accelerometers, that is, accelerometers that can measure n components of point-accelerations, where n = 1, 2, 3. We call these architectures simplectic, as they use n + 1 legs oriented normally to the n + 1 faces of the regular simplex associated with the n-dimensional subspace of measured acceleration components. We show that the simplectic biaxial accelerometer can be fabricated using micromachining MEMS techniques, while the simplectic triaxial accelerometer lends itself to compliant-mechanism fabrication techniques. CAD models of the prototypes proposed are provided for all of the three novel mechanical architectures proposed. Finally, the direct kinematics problems associated with the simplectic biaxial and triaxial accelerometers are shown to be linear in both cases. This feature simplifies the estimation of the proof-mass displacement from piezoresistive or piezoelectric measurements taken at the flexible joints connecting the legs of the mechanism to the rigid body whose acceleration is under estimation.

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.

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 categoriesMeta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Simulation or modeling · Consensus signal: none
GenreCandidate signal: Methods · Consensus signal: none
Teacher disagreement score0.790
Threshold uncertainty score1.000

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 head0.046
GPT teacher head0.294
Teacher spread0.248 · 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