MétaCan
Menu
Back to cohort
Record W3104564324 · doi:10.1115/detc2001/vib-21435

Modeling and Chatter Suppression With Ultra-Precision in Dynamic Turning Metal Cutting Process

2001· article· en· W3104564324 on OpenAlexaff
Jingchuan Pan, Chun‐Yi Su

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldEngineering
TopicAdvanced machining processes and optimization
Canadian institutionsConcordia University
Fundersnot available
KeywordsControl theory (sociology)Displacement (psychology)VibrationMachiningController (irrigation)HysteresisProcess (computing)Machine toolComputer scienceEngineeringMechanical engineeringAcousticsPhysics

Abstract

fetched live from OpenAlex

Abstract In turning metal cutting, the occurrence of self-excited vibration, so called chatter, is undesirable as it gives rise to production problems, causing detrimental effects on the machined surface finish and decreasing the machining efficiency. In this paper, in order for chatter suppression, a piezoactuator is introduced for the regulation of the machine tool displacement and the metal cutting system is modeled as a class of uncertain linear system with hysteresis and time delay. In order to overcome the chatter due to the hysteresis and time delay during the cutting process, an robust adaptive controller for the metal cutting system of ultra-precision is proposed and the simulation results shows that the proposed adaptive controller significantly eliminates the chatter phenomena.

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: Simulation or modeling · Consensus signal: Simulation or modeling
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.472
Threshold uncertainty score0.380

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 head0.005
GPT teacher head0.239
Teacher spread0.234 · 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 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

Citations4
Published2001
Admission routes1
Has abstractyes

Explore more

Same topicAdvanced machining processes and optimizationFrench-language works237,207