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Record W4246583610 · doi:10.1109/papcon.2004.1338379

Commissioning and maintenance testing of multifunction digital relays

2004· article· en· W4246583610 on OpenAlexaff
C. Mozina, M. Young, B. Bailey, B. Baker, G. Dalke, B. Duncan, J. Fischer, D. Love, N. Nichols, C. Normand, L. Padden, A. Pierce, P. Pillai, L. Powell, T. Stringer

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldEngineering
TopicPower Systems Fault Detection
Canadian institutionsUniversity of VictoriaMcMaster UniversityUniversity of Waterloo
Fundersnot available
KeywordsRelayDigital protective relayProtective relayEngineeringProject commissioningElectrical engineeringElectric power systemPower-system protectionFunction (biology)Reliability engineeringComputer sciencePower (physics)Publishing

Abstract

fetched live from OpenAlex

Protective relay technology over the past twenty-five years has evolved from single-function electromechanical (E-M) relays to static (electronic) relays and finally to digital multifunction relays. A significant number of these multifunction digital relays are being installed on medium voltage electric power systems within industrial and commercial facilities. As was required in earlier E-M and static relay technologies, digital relays also require commissioning and relay setting verification. This paper discusses the unique challenges the user faces in testing and commissioning digital multifunction relays. It also explores the impact on maintenance testing of self-diagnostics, the digital relay's internal capability to check itself for failures.

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 machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.004
Version: metacan-v3-hybrid-931329e0061cValidation 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 score0.001
Threshold uncertainty score0.004

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.004
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.000
Science and technology studies0.0000.000
Scholarly communication0.0000.001
Open science0.0010.001
Research integrity0.0010.000
Insufficient payload (model declined to judge)0.0010.000

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 head0.009
GPT teacher head0.187
Teacher spread0.178 · 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 source (direct Gemma or distilled Codex), 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

Citations0
Published2004
Admission routes1
Has abstractyes

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