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Record W2161981373 · doi:10.1109/icpadm.1997.616566

Partial discharge characteristics of artificial defects in mica-epoxy composite materials

2002· article· en· W2161981373 on OpenAlexaff
Kunihiko Itoh, H.G. Sedding

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldMaterials Science
TopicMaterial Properties and Applications
Canadian institutionsHydro One (Canada)
Fundersnot available
KeywordsEpoxyMicaPartial dischargeComposite materialMaterials scienceComposite numberComposite epoxy materialVoltageElectrical engineeringEngineering

Abstract

fetched live from OpenAlex

Partial discharge (PD) in groundwall insulation of rotating machines is mainly caused by internal defects like delaminations or cracks according to microscopic investigation. Discrimination of the cracks from the delaminations is important for diagnosis of the groundwall insulation because the cracks along external electrical field can initiate electrical tree and reduce residual breakdown voltage. PD characteristics of artificial delaminations and cracks were measured with both ultra wideband detection and conventional detection. As a result PD in crack type voids included distinguishing high magnitude pulses with a few ns rise time and 1-10 ns fall time. Delamination type void had two types of waveforms that are characterized by (1) fall time longer than 40 ns and (2) fast rise time and fall time of a few ns. PD characteristics with different conditions of void surface, void dimensions and ventilation are also discussed.

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)0.000
metaresearch head score (Gemma)0.001
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 score0.002

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
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 head0.031
GPT teacher head0.240
Teacher spread0.209 · 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

Citations2
Published2002
Admission routes1
Has abstractyes

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