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Record W2105946606 · doi:10.1109/elinsl.2010.5549547

Comparative evaluation of various grading systems for electric machinery stator windings

2010· article· en· W2105946606 on OpenAlexaff
Saeed Ul Haq, Ramtin Omranipour

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldMaterials Science
TopicHigh voltage insulation and dielectric phenomena
Canadian institutionsGeneral Electric (Canada)
Fundersnot available
KeywordsMaterials scienceLappingComposite materialStatorElectromagnetic coilVoltageSilicon carbideElectrical conductorGrading (engineering)Electrical engineeringEngineering

Abstract

fetched live from OpenAlex

The surface potential characteristics of grading systems of various lengths and configurations used for medium voltage form-wound stator coils have been examined. The grading material used in this investigation was woven polyester fabric tape loaded with a varnish containing a semi-conductive silicon carbide filler. Form-wound stator coils for a machine rating of 13.8 kV (line-to-line) were manufactured. Stress grading tape was applied to the coils using two lapping configurations and with two overall lengths. All sample coils then received a vacuum pressure impregnation (VPI) treatment. The surface field distribution in the stress grading regions of the sample coils was measured at test voltages of 8 kV and 14 kVrms. In addition, the temperature profiles of the grading systems were recorded at applied voltages up to 28.6 kVrms. The experimental results revealed that the stress grading tape lapping configuration has an influence on the field distribution to some degree; however, little or no effect was observed on the field dependent property when the grading length in the endarm region was increased.

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)0.001
metaresearch head score (Gemma)0.002
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.001
Threshold uncertainty score0.003

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.002
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 science0.0000.000
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 head0.042
GPT teacher head0.320
Teacher spread0.279 · 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 designBench or experimental
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

Citations5
Published2010
Admission routes1
Has abstractyes

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