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Record W2883707127 · doi:10.5539/mer.v8n2p1

Influence of Similarity Law on Movement Characteristics of Vibration Actuator

2018· article· en· W2883707127 on OpenAlexvenueno aff
Hiroyuki Yaguchi

Bibliographic record

VenueMechanical Engineering Research · 2018
Typearticle
Languageen
FieldEngineering
TopicSoft Robotics and Applications
Canadian institutionsnot available
Fundersnot available
KeywordsActuatorClimbRotary actuatorVibrationCeiling (cloud)Control theory (sociology)EngineeringMechanical engineeringStructural engineeringAcousticsComputer scienceElectrical engineeringPhysicsAerospace engineering

Abstract

fetched live from OpenAlex

Currently, a belt conveyor or an automatic guided vehicle is used as a conveying device in a factory. However, Transportation of the ceiling surface and the wall surface in these devices is impossible. Elevator is used for conveying from the lower floor to the upper floor. Therefore, the conveying device capable of movement on a wall and a ceiling significantly improves the efficiency of work. Based on this background, development of working robots capable of transporting on a wall surface is required. In the present study, the vibration actuator with a very simple structure capable of movement on a magnetic substance by means of the inertial force of a vibration model was again considered. Furthermore, upsizing for the actuator in order to improve the propulsion characteristics was considered. The volume of the permanent magnet constituting the vibration component of the actuator was increased according to the similarity rule. Four models of actuator with approximately equal drive frequency were prototyped and experimentally tested. The experimental results demonstrate that the maximum efficiency of the actuator for a standard model pulling its own weight was 27.1 %. Furthermore, the actuator is able to pull a load mass of 170 g. For the actuator of 5 times model, the actuator is able to climb upward at 9.5 mm/s while pulling a load mass of 3500 g. This actuator is able to propel a load mass of approximately 36 times the weight of the actuator itself.

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: Empirical
Teacher disagreement score0.239
Threshold uncertainty score0.341

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 head0.031
GPT teacher head0.302
Teacher spread0.271 · 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
Published2018
Admission routes1
Has abstractyes

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