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Record W4285139242 · doi:10.1109/tie.2022.3189099

Power Electronic Converter Based Induction Motor Emulator With Stator Winding Faults

2022· article· en· W4285139242 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.

Bibliographic record

VenueIEEE Transactions on Industrial Electronics · 2022
Typearticle
Languageen
FieldEngineering
TopicReal-time simulation and control systems
Canadian institutionsConcordia University
Fundersnot available
KeywordsStatorInduction motorEngineeringFault (geology)Power (physics)Control engineeringAdjustable-speed driveElectromagnetic coilPower electronicsElectronic engineeringElectrical engineeringComputer scienceVoltage

Abstract

fetched live from OpenAlex

The induction machine (IM) is commonly adopted in the industry, which plays an important role in energy conversion between mechanical and electrical power. This article proposes a power electronic converter based IM power hardware-in-the-loop (PHIL) emulator, which can emulate an IM with internal faults. The risk, time, and cost associated with generating real faults can be reduced, helping to overcome safety issues with actual faulted machines. The technique could also be applied in fault detection, diagnosis, and fault control areas. First, the IM mathematical model with an interturn short circuit of the stator winding is established. Based on that, the PHIL emulator is developed and tested for different interturn short-circuit conditions of an IM. A comparison of the emulator results with simulation results and actual IM results demonstrates the validity of the proposed solution.

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 categoriesMeta-epidemiology (narrow), Insufficient payload (model declined to judge)
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 score0.402
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.002
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 head0.011
GPT teacher head0.201
Teacher spread0.191 · 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