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Record W2916820690 · doi:10.1155/2019/4359524

An Investigation on Speed Control of a Spindle Cluster Driven by Hydraulic Motor: Application to Metal Cutting Machines

2019· article· en· W2916820690 on OpenAlexaff
Ngoc Hai Tran, Cung Le, Anh Dung Ngô

Bibliographic record

VenueInternational Journal of Rotating Machinery · 2019
Typearticle
Languageen
FieldEngineering
TopicHydraulic and Pneumatic Systems
Canadian institutionsÉcole de Technologie Supérieure
Fundersnot available
KeywordsControl theory (sociology)Overshoot (microwave communication)PID controllerComputer scienceHydraulic motorElectronic speed controlController (irrigation)Rotational speedInertiaFuzzy logicHydraulic machineryControl engineeringMechanical engineeringPhysicsEngineering

Abstract

fetched live from OpenAlex

In this article, we present an experimental study on the speed stability of a spindle driven by a hydraulic motor, which is controlled by a proportional valve, through a V-belt transmission. The research includes the dynamic modeling of the transmission cluster and the transmission from the hydraulic motor to the working shaft via V-belt mechanism, together with the establishment of a mathematical model and fuzzy self-tuning PID controller model. In the model, the V-belt is assumed as an elastic module, and the friction coefficient and mass inertia moment of the hydraulic motor are considered as constant. The Matlab software is used to simulate the speed response of the hydraulic motor to the working shaft. Based on theoretical study, we resemble the experimental system and determine the parameters for the fuzzy self-tuning PID controller. We conduct experiment and investigate the speed stability of the working shaft from 300 to 1100 (rpm) based on transient response parameters such as the time delay, the setting time, the overshoot, and the rotation error at steady state. Thereby, in this study, the simulation and the experiment results are compared and evaluated regarding the speed stability of the working shaft driven by hydraulic motor transmitted through V-belt mechanism. The findings show the speed controllability by using proportional valve to manipulate the oil flow and applying a self-tuning PID controller to achieve very good results such as the error difference of 0.001 to 0.036%, the delay of 0.01 to 0.02 seconds, no overshoot, and the settling error less than 5% compared to the set values. On the other hand, we include the effect of the oil temperature of 40 to 80°C on the working shaft speed (500, 900 rpm) in this study and derive that the system works well at temperature range of 40 to 70°C. On these findings, we propose the applicability of this system on the current machinery cutters. In addition, we verify the effects of the hydraulic drive for main shaft, controlled by fuzzy PID, by comparison of the roughness of the machining work piece with respect to the one using the 3-phase motor drive.

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: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.001
Threshold uncertainty score0.003

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
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)0.0010.000

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 head0.007
GPT teacher head0.241
Teacher spread0.235 · 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 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

Citations5
Published2019
Admission routes1
Has abstractyes

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