MétaCan
Menu
Back to cohort
Record W2073972662 · doi:10.1109/ccece.2010.5575192

Impedance-based ground fault location for transmission lines

2010· article· en· W2073972662 on OpenAlexaff
Hongling Sun, Vijay K. Sood

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldEngineering
TopicPower Systems Fault Detection
Canadian institutionsOntario Tech University
Fundersnot available
KeywordsFault (geology)ReactanceEmtpElectrical impedanceTransmission lineSuperposition principleMATLABElectronic engineeringComputer scienceElectric power transmissionEngineeringTerminal (telecommunication)VoltageElectric power systemElectrical engineeringPower (physics)TelecommunicationsMathematics

Abstract

fetched live from OpenAlex

Impedance-based fault location methods are widely used due to their simple mode of operation and relatively low cost. However, their performance suffers from factors such as fault impedance, pre-fault load current, and remote infeed. Although significant improvements have been made by compensating these effects, the presence of unreliable zero-sequence current always presents a challenge to those conventional methods. The algorithm proposed in this paper for a one-terminal fault location method using a new superposition current in conjunction with a reactance method offers significant improvement. Different types of line modeling are represented to show their effects on the fault location estimation. Furthermore, comparative test results of the proposed one-terminal method with conventional two-terminal methods are also presented. The simulations are performed in EMTP-RV and the signal processing is conducted by using MATLAB.

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: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.840
Threshold uncertainty score0.356

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 head0.008
GPT teacher head0.238
Teacher spread0.230 · 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

Citations3
Published2010
Admission routes1
Has abstractyes

Explore more

Same topicPower Systems Fault DetectionFrench-language works237,207