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Record W3125843953 · doi:10.1115/msec2020-8452

Structural Nonlinearity of Robotic Machining Systems

2020· article· en· W3125843953 on OpenAlexaff
Yaser Mohammadi, Keivan Ahmadi

Bibliographic record

VenueVolume 2: Manufacturing Processes; Manufacturing Systems; Nano/Micro/Meso Manufacturing; Quality and Reliability · 2020
Typearticle
Languageen
FieldEngineering
TopicAdvanced machining processes and optimization
Canadian institutionsUniversity of Victoria
Fundersnot available
KeywordsMachiningVibrationNonlinear systemModalControl theory (sociology)Frequency responseRobotModal analysisHarmonicMachine toolEngineeringAmplitudeComputer scienceControl engineeringMechanical engineeringStructural engineeringAcousticsPhysicsMaterials scienceArtificial intelligenceControl (management)Optics

Abstract

fetched live from OpenAlex

Abstract Excessive and unstable vibrations that are caused by the machining forces are among the most critical problems that limit the use of industrial robots instead of CNC machine tools. Reduction and control of robot’s vibrations during machining require accurate models of the robot’s vibration response to the dynamic forces exerted at the Tool Centre Point (TCP) where the cutting tool interacts with the workpiece material. The existing models of vibrations in robotic machining have been formed by assuming the linearity of the dynamic response at the TCP. In this paper, the accuracy of this assumption is investigated experimentally, and the results show that the dynamic response at the TCP is strongly nonlinear. An experimental procedure is presented to identify the nonlinearities by employing the first-order Frequency Response Functions (FRFs) measured using various input force excitations. Nonlinear Complex Mode Analysis is then used to extract the modal parameters of the system when its dynamics is linearized around a harmonic response with a constant amplitude. The extracted modal parameters strongly depend on the amplitude of the applied force and the resulting vibrations. This study highlights the need for considering the nonlinearities of the structural dynamics of industrial robots in modelling machining vibrations.

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)0.002
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow)
Consensus categoriesMeta-epidemiology (narrow)
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Simulation or modeling · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.837
Threshold uncertainty score0.999

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.001
Meta-epidemiology (narrow)0.0020.002
Meta-epidemiology (broad)0.0030.000
Bibliometrics0.0000.000
Science and technology studies0.0010.001
Scholarly communication0.0010.002
Open science0.0010.001
Research integrity0.0010.002
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 head0.021
GPT teacher head0.251
Teacher spread0.230 · 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; both teacher heads agree on what is shown here.

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

Citations5
Published2020
Admission routes1
Has abstractyes

Explore more

Same venueVolume 2: Manufacturing Processes; Manufacturing Systems; Nano/Micro/Meso Manufacturing; Quality and ReliabilitySame topicAdvanced machining processes and optimizationFrench-language works237,207