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Record W2142145002 · doi:10.1109/pess.2000.868731

A fast distance relay using adaptive data window filters

2002· article· en· W2142145002 on OpenAlex
T.S. Sidhu, D.S. Ghotra, Manoj Sachdev

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
TopicPower Systems Fault Detection
Canadian institutionsUniversity of Saskatchewan
Fundersnot available
KeywordsRelayDigital protective relayFault (geology)PhasorWindow (computing)TrippingComputer scienceProtective relayTransient (computer programming)Filter (signal processing)Solid-state relayElectronic engineeringControl theory (sociology)Electric power systemPower (physics)Real-time computingCircuit breakerEngineeringElectrical engineering

Abstract

fetched live from OpenAlex

This paper describes the design of a distance relay that, uses adaptive data window filters to provide high speed tripping. The relay uses a fault detector to detect the inception of a fault. Starting from the fault detection, the data window size is progressively increased as new fault samples become available until the window size becomes one cycle of the fundamental frequency. At each instant, a suitable filter is used for estimating voltage and current phasors. This procedure improves the transient response of the relay and allows faster convergence of the impedance estimates and, therefore, reduces the trip time. The proposed relay was tested by using fault simulations on a sample power system. Results indicate that the proposed relay design reduces the trip times.

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: Simulation or modeling · Consensus signal: Simulation or modeling
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.974
Threshold uncertainty score0.444

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 head0.064
GPT teacher head0.236
Teacher spread0.172 · 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

Quick stats

Citations10
Published2002
Admission routes1
Has abstractyes

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