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Record W4295094986 · doi:10.3390/vibration5030034

Vibration Analysis of a 5-DOF Long-Reach Robotic Arm

2022· article· en· W4295094986 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

VenueVibration · 2022
Typearticle
Languageen
FieldEngineering
TopicSoil Mechanics and Vehicle Dynamics
Canadian institutionsUniversity of Saskatchewan
FundersNatural Sciences and Engineering Research Council of CanadaCollege of Agriculture and Bioresources, University of SaskatchewanCanada First Research Excellence FundUniversity of Saskatchewan
KeywordsFinite element methodVibrationModal analysisNatural frequencyRobotic armModalAccelerationSoftwareNormal modeAcousticsDegrees of freedom (physics and chemistry)Structural engineeringComputer scienceEngineeringMechanical engineeringPhysicsMaterials science

Abstract

fetched live from OpenAlex

In this paper, dynamic and vibration characteristics of a newly developed 5-degrees-of-freedom (5-DOF) long-reach robotic arm for farm applications is studied through finite element analysis (FEA), as well as experimentally. The new manipulator is designed to be light and compact enough that it can be mounted on a small vehicle for farm applications. A finite element model of this novel manipulator was established using a commercial FEA software. FEA was carried out for two different configurations of the manipulator (fully-extended and vertical half-extended). The fully-extended configuration provides the longest reach of the arm and is one of the most commonly used poses in farm applications; vibrations of this configuration are highly affected by its base excitation. The FEA results indicated that the first six natural frequencies of the manipulator for the two configurations considered were between 4.4 to 41.6 (Hz). Modal analysis on the fully-extended configuration was completed using experimental modal analysis to verify the finite element results. In the experiments, acceleration data were obtained utilizing sensors, and were post-processed using Fast-Fourier Transforms. The first six natural frequencies and their corresponding mode shapes were obtained using FEA and also experimentally, and the results were compared; the comparison showed good agreement, with less than 10% difference. Our verified FE model provides a reliable basis for future vibration control for the newly developed robotic arm for different applications. A harmonic response simulation was also carried out using an experimentally corrected FE model; this provides a good understanding of the dynamic behavior of the newly developed arm under base excitation. This paper offers an experimentally corrected FEA model for a large manipulator with base excitation for farm applications.

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 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: Empirical
Teacher disagreement score0.304
Threshold uncertainty score0.328

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
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 head0.009
GPT teacher head0.207
Teacher spread0.198 · 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