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Record W4287846833 · doi:10.1109/eic51169.2022.9833158

Correction Factor for Insulation Resistance of Salient Poles

2022· article· en· W4287846833 on OpenAlexaff
Joel Pedneault-Desroches, Simon Bernier, Hélène Provencher

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldEngineering
TopicPower Transformer Diagnostics and Insulation
Canadian institutionsCégep Saint-Jean-sur-RichelieuHydro-Québec
Fundersnot available
KeywordsStatorRotor (electric)Materials scienceComposite materialElectromagnetic coilEpoxyThermosetting polymerMechanical engineeringElectrical engineeringEngineering

Abstract

fetched live from OpenAlex

Resistance of insulating material is known to be temperature dependent, the resistance decreasing as the temperature goes up. When applied to rotating machines, there is a need to establish a reference criterion of acceptance. For the resistance of an insulating material, the reference temperature is 313 K (40 °C). Depending on the insulation system, the correction factor will differ. The correction factors proposed in standard 43-2013 for thermoplastic and thermoset materials recommended for machine windings are given although it is a stator or a rotor winding. Even if the insulation system of a rotor salient pole can be composed today of epoxy (thermoset), it is slightly different from the insulation system of the stator winding, and to our knowledge it has never been proven that the same temperature correction applies to stators and rotors. The goal of this study is to present results of the insulation resistance of rotor salient poles as a function of the temperature and verify if a new correction factor is better suited for the rotor winding insulation system. To achieve this, experimental data of insulation resistance (IR) vs temperature will be shown for aramid paper and NEMA G11 insulation material. Experience with real rotor poles equipped with Fiber Bragg Grating (FBG) measurement systems and laboratory results on typical rotor insulation material will be presented. The results show that NEMA G11 material needs new correction factors based on the results.

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 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: Simulation or modeling · Consensus signal: Simulation or modeling
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.351
Threshold uncertainty score0.168

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 head0.010
GPT teacher head0.213
Teacher spread0.203 · 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 teacher head, 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

Citations4
Published2022
Admission routes1
Has abstractyes

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