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Record W2909331547 · doi:10.1109/tec.2019.2891349

A Universal High-Frequency Induction Machine Model and Characterization Method for Arbitrary Stator Winding Connections

2019· article· en· W2909331547 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.
fundA Canadian funder is recorded on the work.

Bibliographic record

VenueIEEE Transactions on Energy Conversion · 2019
Typearticle
Languageen
FieldEngineering
TopicElectromagnetic Compatibility and Noise Suppression
Canadian institutionsOkanagan University CollegeUniversity of British Columbia, Okanagan CampusUniversity of British ColumbiaUniversity of Manitoba
FundersNatural Sciences and Engineering Research Council of Canada
KeywordsStatorElectrical impedanceOvervoltageInduction motorElectromagnetic coilEquivalent circuitControl theory (sociology)VoltageFrequency responseEngineeringElectronic engineeringComputer scienceTopology (electrical circuits)Electrical engineering

Abstract

fetched live from OpenAlex

High-frequency modeling of induction machines plays an important role in investigating motor drive electromagnetic interference issues such as stator winding reflected-wave overvoltage and bearing discharging current. Characterization of high-frequency machine models requires measurements of machine's differential-mode (DM) and common-mode (CM) impedances up to tens of MHz. The machine's stator winding connections, e.g., single-, and series-, parallel-winding Y/Δ configurations, influence the measured DM and CM impedances and model parameters. In this paper, a universal high-frequency equivalent circuit model capable of representing induction machines with arbitrary stator winding connections is proposed. The new model features a simple structure with a straightforward characterization method. Specifically, only one stator winding configuration is required for impedance measurements to fully characterize the machine model for arbitrary stator winding connections. The proposed methodology is demonstrated using a 7.5 hp dual-voltage nine-terminal/lead induction machine and a drive system. The simulated DM and CM impedances as well as the motor overvoltages show excellent agreement with the experimental results. The proposed model and characterization method represent significant improvement in terms of accuracy, applicability/generality, and convenience compared to prior conventional models.

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.

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: Bench or experimental · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.655
Threshold uncertainty score0.760

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 head0.007
GPT teacher head0.202
Teacher spread0.195 · 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