MétaCan
Menu
Back to cohort
Record W2085645289 · doi:10.1109/pcicon.2003.1242613

The effect of surge testing on the voltage endurance life of stator coils

2003· article· en· W2085645289 on OpenAlexaff
J.H. Dymond, Meredith K. W. Stranges, N. Stranges

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldMaterials Science
TopicHigh voltage insulation and dielectric phenomena
Canadian institutionsGeneral Electric (Canada)
Fundersnot available
KeywordsStatorElectromagnetic coilVoltageSurgeTransient (computer programming)OvervoltageElectrical engineeringHigh voltageMaterials scienceBreakdown voltageInsulation systemGenerator (circuit theory)Dielectric strengthTransient voltage suppressorEngineeringStructural engineeringPower (physics)Computer sciencePhysics

Abstract

fetched live from OpenAlex

Surge tests with short rise times are used to ensure turn insulation integrity in dry vacuum-pressure impregnated (VPI) coils. The use of this test migrated from the evaluation of low voltage random wound stators and fully processed generator bars. The dielectric properties of dry (unimpregnated) VPI coils are not fully developed. Application of a high voltage transient electric field in uncured or partially processed coils may initiate insulation damage. This damage may shorten the life of the insulation system after complete impregnation and cure. This paper presents a series of laboratory tests and finite element simulations examining the applied test voltage and number of applied pulses as factors in determining the risk of using surges as a manufacturing proof test on unimpregnated coils. Potential failure initiation sites can be linked to the test voltage as a more significant factor than the number of pulses applied. The sympathetic voltage response in a single coil as a function of location within a winding is described for a 20-pole stator undergoing green surge testing as part of a quality assurance program. Voltage endurance testing and sample dissection data are presented to show that the voltage endurance test life of the coils after complete processing is shortened by the surge test.

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)0.004
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 score0.004

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.004
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)0.0010.000

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 head0.018
GPT teacher head0.237
Teacher spread0.219 · 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

Citations1
Published2003
Admission routes1
Has abstractyes

Explore more

Same topicHigh voltage insulation and dielectric phenomenaFrench-language works237,207