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Record W2102099568 · doi:10.1109/tdei.2012.6148503

Contribution of humidity to the evolution of slot partial discharges

2012· article· en· W2102099568 on OpenAlexaff
Mélanie Lévesque, Éric David, C. Hudon, M. Bélec

Bibliographic record

VenueIEEE Transactions on Dielectrics and Electrical Insulation · 2012
Typearticle
Languageen
FieldMaterials Science
TopicHigh voltage insulation and dielectric phenomena
Canadian institutionsHydro-QuébecÉcole de Technologie Supérieure
Fundersnot available
KeywordsHumidityPartial dischargeAnalytical Chemistry (journal)Phase (matter)Relative humidityMaterials scienceElectrical engineeringPhysicsThermodynamicsChemistryVoltageChromatographyEngineering

Abstract

fetched live from OpenAlex

The impact of humidity on the slot partial discharge (PD) process was evaluated in a laboratory experiment conducted in a climatic chamber under constant humidity and temperature. Two stator bars, subjected to slot PDs at two temperatures (28°C and 85°C), were aged at twice their nominal phase-to-ground voltage (16 kV) under three absolute humidity levels (5 g/m <sup xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">3</sup> , 9 g/ <sup xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">3</sup> and 13 g/ <sup xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">3</sup> ). The phase resolved partial discharge (PRPD) patterns were monitored during short aging sequences and visual observations of the surfaces were made at the beginning and end of each aging sequence. Observation confirms that humidity has a significant impact on the discharge phenomenon but other parameters, such as surface condition and temperature, affected the discharge process just as much. This paper presents the way slot PD activity evolves and affects the related PRPD pattern under different conditions of humidity, temperature and surface degradation.

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)0.001
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: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.443
Threshold uncertainty score0.456

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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 head0.017
GPT teacher head0.255
Teacher spread0.238 · 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 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

Citations28
Published2012
Admission routes1
Has abstractyes

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