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Record W2755556797 · doi:10.1109/tdei.2017.006181

A study on PD activities of oil-impregnated paper under pulse voltages using gas analysis

2017· article· en· W2755556797 on OpenAlexaff
Mahdi Khanali, Shesha Jayaram

Bibliographic record

VenueIEEE Transactions on Dielectrics and Electrical Insulation · 2017
Typearticle
Languageen
FieldMaterials Science
TopicHigh voltage insulation and dielectric phenomena
Canadian institutionsUniversity of Waterloo
Fundersnot available
KeywordsVoltageImpulse (physics)TransformerMaterials scienceNuclear engineeringHigh voltageElectrical engineeringTransformer oilHydrogenAcousticsEnvironmental scienceEngineeringAutomotive engineeringChemistryPhysics

Abstract

fetched live from OpenAlex

Gassing problems and premature insulation failures in wind turbine transformers indicate reliability concerns about the insulation of such components. This fact necessitates investigating degradation of transformer insulation systems under high-dV/dt pulse voltages that exist in today's wind energy plants. For this purpose, PD activity, generally assumed to be the main long-term cause of insulation deterioration, needs to be analyzed. This work evaluates the effects of impulse voltage parameters such as rate of rise and repetition frequency on inception voltage and intensity of PD activities. PD parameter measurement under high-dV/dt voltages is challenging due to interferences from fast oscillations, and difficulties of PD energy measurements. To avoid such issues, which are related to electromagnetic detection methods under pulse energization, this work uses a chemical approach to compare PD activities, based on the rate of hydrogen generation in a controlled test chamber with oil/paper samples. Gas monitoring of the oil containing impregnated paper samples reveals that a faster rate of rise increases PD energy as well as inception voltage. Results based on experiments conducted in small oil chambers show good correlation between the amount of hydrogen detected and PD energy level; hence it can be used as a benchmark for comparing PD energy levels under various impulse waveforms.

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 categoriesMeta-epidemiology (narrow)
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 score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0010.001
Science and technology studies0.0010.000
Scholarly communication0.0000.001
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 head0.042
GPT teacher head0.303
Teacher spread0.262 · 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.

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

Citations16
Published2017
Admission routes1
Has abstractyes

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