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Design of the Servo Control System Based on EtherCAT P

2021· article· en· W3171789988 on OpenAlexaff
Qiang Hua, Yunchang Yao, Weigang Zhou, Lingyu Kong, Anhuan Xie, Zhihui Zhou, Dan Zhang

Bibliographic record

VenueJournal of Physics Conference Series · 2021
Typearticle
Languageen
FieldComputer Science
TopicNetwork Time Synchronization Technologies
Canadian institutionsYork University
Fundersnot available
KeywordsIndustrial EthernetServo controlServoServomotorEmbedded systemEthernetServo driveControl systemMotion controlSoftwareReliability (semiconductor)Computer scienceComputer hardwareControl engineeringRobotPower (physics)EngineeringElectrical engineering

Abstract

fetched live from OpenAlex

Abstract EtherCAT is fully compliant with Ethernet standards, with 100Mbps transfer speed and good synchronization. It is widely used in the industrial field, such as the servo control system, robots, and numerical control machine tool. There are still lots of wires for power and communication in these applications, especially in the complex multi-axis system, leading to high installation cost and poor reliability. In this paper, a novel servo control system based on EtherCAT P is proposed. The EtherCAT P technology is an addition to EtherCAT, which can enable the standard 4-wire Ethernet cable to transmit not only data but also two electrically isolated power supplies. The hardware design and software architecture of the servo control system are described including servo motor controller, powered device, and power sourcing devices. A servo control system with one servo slave and TwinCAT master is built and some tests are carried out. The experimental results verify the power supply capacity, stability, and motor control functions.

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)0.000
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: none
Teacher disagreement score0.003
Threshold uncertainty score0.011

Distilled classifier scores by category (both heads)

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 science0.0010.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0030.001

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 head0.020
GPT teacher head0.212
Teacher spread0.192 · 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
Published2021
Admission routes1
Has abstractyes

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