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Record W2152305440 · doi:10.1109/ias.2004.1348385

Starting and vector control of series-connected wound-rotor induction motor in super synchronous mode

2004· article· en· W2152305440 on OpenAlexaff
Essam M. Rashad, T.S. Radwan, M.A. Rahman

Bibliographic record

VenueConference Record of the 2004 IEEE Industry Applications Conference, 2004. 39th IAS Annual Meeting. · 2004
Typearticle
Languageen
FieldEngineering
TopicElectric Motor Design and Analysis
Canadian institutionsMemorial University of Newfoundland
Fundersnot available
KeywordsWound rotor motorControl theory (sociology)Induction motorVector controlStatorSynchronous motorRotor (electric)Direct torque controlTorqueAC motorComputer scienceMagnetomotive forceEngineeringControl engineeringPhysicsElectric motorVoltageControl (management)Electrical engineeringArtificial intelligence

Abstract

fetched live from OpenAlex

When the stator and rotor windings of a wound rotor induction machine are connected in series, electromechanical energy conversion is possible provided that the phase sequence of the rotor magnetomotive force is in the reverse sense to that of the stator. As a motor, the series-connected induction motor (SCIM) can operate at exactly double the synchronous speed for stable ranges of operation. The conventional super synchronous SCIM suffers from the absence of starting torque, and it has stability problems. In order to overcome the inherent starting and operating problems a novel vector control based technique has been proposed to achieve self-starting and stable operation for the SCIM. It has been shown both analytically and experimentally that the SCIM has higher torque capabilities compared to those obtained from a typical wound rotor induction motor.

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: Simulation or modeling · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.001
Threshold uncertainty score0.004

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 science0.0000.000
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 head0.012
GPT teacher head0.225
Teacher spread0.213 · 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 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

Citations10
Published2004
Admission routes1
Has abstractyes

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Same venueConference Record of the 2004 IEEE Industry Applications Conference, 2004. 39th IAS Annual Meeting.Same topicElectric Motor Design and AnalysisFrench-language works237,207