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The Eroding DBA Detection in AC Inclined Plane Tracking and Erosion Test Using UHF Antenna

2024· article· en· W6903383916 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldEngineering
TopicElectrical Fault Detection and Protection
Canadian institutionsNational Research Council CanadaUniversity of Waterloo
Fundersnot available
KeywordsElectric arcFrequency bandFrench hornUltra high frequencySilicone rubberIntensity (physics)ErosionInclined planeTracking (education)Partial discharge

Abstract

fetched live from OpenAlex

In this work, ultra-high frequency detection of eroding dry band arcing is employed as an online and non-intrusive technique to identify deep erosion failure during the AC inclined plane test. To this end, tests are conducted on silicone rubber under three different voltages, while simultaneously measuring leakage current, surface temperature, and ultra-high frequency signals using a horn antenna. No ultra-high frequency detection is obtained during the mild dry band arcing in the test, which does not lead to erosion. In contrast, detection becomes evident during stable dry-band arcing activity, particularly when the intensity becomes significant. Ultra-high frequency measurements indicate that the intensity of detection increases with the severity of eroding dry-band arcing during the test and with higher test voltages.

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.

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: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.828
Threshold uncertainty score0.310

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
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 head0.016
GPT teacher head0.250
Teacher spread0.235 · 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