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Record W2352605288

Research on Partial Discharge Detection and Location of Switchgear Based on TEV and Ultrasonic Wave Methods

2013· article· en· W2352605288 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

VenueElectrical Measurement & Instrumentation · 2013
Typearticle
Languageen
FieldEngineering
TopicPower Line Inspection Robots
Canadian institutionsNortel (Canada)
Fundersnot available
KeywordsPartial dischargeSwitchgearUltrasonic sensorVoltageAcousticsReliability (semiconductor)High voltageEngineeringElectrical engineeringPower (physics)Physics
DOInot available

Abstract

fetched live from OpenAlex

The safe and reliable operation of high voltage(HV)switchgear directly influences the reliability of the whole substation's power supply, so the partial discharge detection of HV switchgear is particularly important. This paper mainly analyzes the principle of transient earth voltage(TEV) and ultrasonic wave methods of partial discharge detection of HV switchgear, and the advantages and disadvantages of these two methods. Four typical models of partial discharge, namely needle plate discharge, internal discharge, suspended discharge and surface discharge, are designed; and an experimental platform of partial discharge detection based on the combination of TEV and ultrasonic wave is designed. Through simulation experiments, the combination of TEV and ultrasonic wave methods is used to locate the orientation of the partial discharge source. This method is verified to be more accurate and practical for partial discharge detection.

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)0.001
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 score0.330
Threshold uncertainty score0.563

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 head0.061
GPT teacher head0.328
Teacher spread0.267 · 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