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Record W2118426790 · doi:10.1109/elinsl.1988.13919

A system for the detection and location of partial discharges using X-rays

2003· article· en· W2118426790 on OpenAlexaff
S. Rizzetto, Noboru Fujimoto, G.C. Stone

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldMaterials Science
TopicHigh voltage insulation and dielectric phenomena
Canadian institutionsHydro One (Canada)
Fundersnot available
KeywordsPartial dischargeSwitchgearVoltageNoise (video)High voltageMaterials sciencePreamplifierSIGNAL (programming language)Sensitivity (control systems)Electrical engineeringModulation (music)Computer scienceOpticsPhysicsElectronic engineeringOptoelectronicsAcousticsAmplifierEngineering

Abstract

fetched live from OpenAlex

A measuring system has been designed which has an enhanced ability to detect partial discharges (PDs) and locate their origin in large epoxy castings. The enhancement is primarily based on the application of X-rays during high voltage testing, which reduces the apparent inception voltage and increases the pulse repetition rate. A high PD signal-to-noise ratio is achieved by using a combination of several techniques, including; a differential (balanced bridge) measuring scheme: detecting PD in the GHz frequency range; use of a lossy transmission line between the power supply and the test specimen to attenuate external noise; and modulation of the X-ray beam. The PD sites are located by scanning the X-ray beam. The system can test 138-kV-class epoxy spacers used in gas-insulated switchgear (GIS). Test voltages up to 500 kV can be achieved with a reliable PD sensitivity of less than 0.1 pC in a typical industrial environment.< <ETX xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">&gt;</ETX>

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: none
Teacher disagreement score0.514
Threshold uncertainty score0.089

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 head0.025
GPT teacher head0.253
Teacher spread0.228 · 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

Citations23
Published2003
Admission routes1
Has abstractyes

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