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INVESTIGATION OF THE ARC ACTIVITY ON HIGH-VOLTAGE POLYMERIC INSULATORS

2011· article· en· W2329199070 on OpenAlexvenueno aff
C. Muniraj, S. Chandrasekar

Bibliographic record

VenueInternational Journal of Power and Energy Systems · 2011
Typearticle
Languageen
FieldMaterials Science
TopicHigh voltage insulation and dielectric phenomena
Canadian institutionsnot available
Fundersnot available
KeywordsArc (geometry)Materials scienceComposite materialElectrical engineeringEngineeringMechanical engineering

Abstract

fetched live from OpenAlex

This paper presents the investigation of dry band and arc activity on silicon rubber insulator based on leakage current characteristics due to pollution under different climatic conditions. In this paper, laboratory-based pollution performance tests were conducted on 11 kV silicon rubber polymeric insulator by applying sodium chloride as pollutant with different pollution levels under AC voltage. Leakage current waveforms during the experimental studies were measured. Normally FFT spectrum estimation method is used to find the harmonic spectrum in the leakage currents. But this method suffers from the major problem of resolution. So in this paper a higher order spectrum estimation method (Min-Norm) was used to study the frequency domain characteristics of the leakage current signal. The results of the Min-Norm harmonic spectrum shows that it has a better resolution than FFT spectrum, and reported results of this initial study on 11 kV silicon rubber insulator shows that formation of dry band and arc due to conducting pollution layer could be easily identified from the analysis of harmonic components magnitude of leakage current signal.

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 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 score0.270
Threshold uncertainty score0.217

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
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)0.0000.000

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 head0.213
Teacher spread0.196 · 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

Citations2
Published2011
Admission routes1
Has abstractyes

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