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Record W2098314841 · doi:10.1109/tpwrd.2007.905550

Real-Time Sag Monitoring System for High-Voltage Overhead Transmission Lines Based on Power-Line Carrier Signal Behavior

2008· article· en· W2098314841 on OpenAlexaff
Wernich de Villiers, Johannes Hendrik Cloete, L.M. Wedepohl, A. F. Burger

Bibliographic record

VenueIEEE Transactions on Power Delivery · 2008
Typearticle
Languageen
FieldPhysics and Astronomy
TopicLightning and Electromagnetic Phenomena
Canadian institutionsUniversity of ManitobaUniversity of British Columbia
Fundersnot available
KeywordsElectric power transmissionOverhead (engineering)EngineeringOverhead lineTransmission lineVoltage sagPower-line communicationElectronic engineeringSIGNAL (programming language)VoltageElectrical engineeringLine (geometry)Electric power systemElectrical conductorAmplitudePower (physics)ConductorComputer sciencePhysicsMaterials scienceOpticsPower quality

Abstract

fetched live from OpenAlex

A new method of measuring the change in the average height above ground of horizontal high-voltage overhead transmission-lines (OHTLs) phase conductors is introduced. The new technique, called power-line carrier sag (PLC-SAG) for short, determines average overhead conductor height variations in real time by correlating sag with measured variations in the amplitude of signals propagating between power-line carrier (PLC) stations. The multifrequency PLC-SAG monitoring signals are injected onto the operational PLC system in the 50- to 500-kHz band, but without interfering with the operational integrity of the PLC teleprotection system. The feasibility of the method was examined using the theory of natural modes for multiconductor systems, and tested by extensive field experiments on two horizontal 400-kV lines operated in South Africa by Eskom. It is concluded that the average height of a horizontal OHTL can be tracked accurately for continuous periods by the PLC-SAG technique.

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)0.000
metaresearch head score (Gemma)0.001
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 score0.002

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
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)0.0010.000

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 head0.011
GPT teacher head0.225
Teacher spread0.214 · 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

Citations57
Published2008
Admission routes1
Has abstractyes

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