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Magnetic Flux Analysis Of Synchronous Machines With Salient Poles

2022· article· en· W4306148165 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

Venue2022 International Conference on Electrical Machines (ICEM) · 2022
Typearticle
Languageen
FieldEngineering
TopicNon-Destructive Testing Techniques
Canadian institutionsÉcole de Technologie SupérieureHydro-Québec
Fundersnot available
KeywordsStatorMagnetic fluxMagnetic circuitPermanent magnet synchronous generatorAir gap (plumbing)Magnetic fieldMagnetic reluctanceRotor (electric)Voltage dropControl theory (sociology)SalientElectrical engineeringComputer scienceEngineeringMechanicsPhysicsVoltageMagnetMaterials science

Abstract

fetched live from OpenAlex

This paper compares the pole drop test and magnetic flux measurement approach for large hydro generator to diagnosis any rotor short circuit in large hydro generator. The pole drop test was conducted according to the IEEE standards. Three different algorithms have been used to analyze the air gap magnetic field obtained from the measurement obtained by the inductive probe installed in the stator bore. The proposed algorithms based of the magnetic flux values of each pole are also used to diagnose inter turns short circuit. The advantages and limitations of the algorithms were explained and compared to the results of the pole drop test on a large hydrogenerator.

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: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.891
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
Bibliometrics0.0010.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0010.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0040.000

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 head0.013
GPT teacher head0.254
Teacher spread0.241 · 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