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Record W2386166483

Application of expert system in distinguishing the fault type and the fault location on the transmission lines of power distribution system

2001· article· en· W2386166483 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

VenueRelay · 2001
Typearticle
Languageen
FieldEngineering
TopicPower Systems and Technologies
Canadian institutionsWestern University
Fundersnot available
KeywordsFault (geology)Fault indicatorInterpolation (computer graphics)Stuck-at faultPoint (geometry)Line (geometry)Fault modelTransmission lineElectric power transmissionComputer scienceEngineeringReal-time computingFault detection and isolationArtificial intelligenceMathematicsElectrical engineeringTelecommunications
DOInot available

Abstract

fetched live from OpenAlex

This paper classifies and distinguishes the fault type of the distribution system by the analysis of the non grounded fault characteristics and using expert system and CLIPS.If the single line fault is detected,it will locate the distance of the fault from the bus using the interpolation method.When we use the interpolation method to locate the fault point,the model of the transmission is the distribution parameter model,considering fully the influence of the distribution capacitance of the transmission line on fault location.This fault location method can locate the fault point accurately,the accuracy of the fault location is 5%.For the transmission line of distribution system,the fault location method proposed in this paper is feasible.

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: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.716
Threshold uncertainty score0.158

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 head0.007
GPT teacher head0.211
Teacher spread0.204 · 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