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Record W4220718890 · doi:10.18280/mmep.090134

Mathematical Description and Study of the Vibration Deck of a Grain Sorting Machine

2022· article· en· W4220718890 on OpenAlexvenueno aff
Ildar Badretdinov, Салават Мударисов, Eduard Khasanov, Salavat Akchurin

Bibliographic record

VenueMathematical Modelling and Engineering Problems · 2022
Typearticle
Languageen
FieldEngineering
TopicAgricultural Engineering and Mechanization
Canadian institutionsnot available
Fundersnot available
KeywordsDeckSortingVibrationKinematicsMechanism (biology)AccelerationDisplacement (psychology)Computer scienceStiffnessEngineeringStructural engineeringMechanical engineeringAcousticsPhysicsClassical mechanicsAlgorithm

Abstract

fetched live from OpenAlex

This article presents the results of a study of the vibrations of the deck of a pneumatic sorting machine. The purpose of this work is to describe the design and technological parameters of the soundboard for the implementation of a mathematical model of the technological process of the grain sorting machine. A kinematic study of the flat hinge mechanism of the deck of a grain sorting machine has been carried out, for which all geometric dimensions are known and the laws of motion of the leading link-the electric drive of the deck based on an asynchronous electric motor – have been determined. As a result, the following were determined: kinematic modes of deck vibrations under various technological conditions; the laws of motion of all links of the deck mechanism, displacement, speed and acceleration of the driven links; a mathematical model of the kinematic scheme of the deck of a grain sorting machine driven by an asynchronous electric motor has been developed.

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)0.000
metaresearch head score (Gemma)0.001
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Simulation or modeling · Consensus signal: Simulation or modeling
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.004
Threshold uncertainty score0.012

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0010.000
Science and technology studies0.0000.001
Scholarly communication0.0010.001
Open science0.0010.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0040.001

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.

Opus teacher head0.016
GPT teacher head0.174
Teacher spread0.158 · 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 designSimulation or modeling
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

Citations1
Published2022
Admission routes1
Has abstractyes

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