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A Novel Zero-Crossing Point Calibration-Based Data Synchronization Approach for an Underground Cable Fault Localization Platform

2022· article· en· W4313562699 on OpenAlexaff
Md Salauddin, Tongkun Lan, C. Y. Chung, Seok‐Bum Ko, Seyed Mahdi Mazhari

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldEngineering
TopicPower Systems Fault Detection
Canadian institutionsUniversity of Saskatchewan
Fundersnot available
KeywordsGlobal Positioning SystemSynchronization (alternating current)Fault (geology)Zero crossingComputer sciencePoint (geometry)Real-time computingCalibrationPrecise Point PositioningConstraint (computer-aided design)Level crossingEngineeringElectrical engineeringTelecommunicationsGeologyGNSS applicationsVoltagePhysics

Abstract

fetched live from OpenAlex

The double-ended measurement-based approach has been widely incorporated in the underground fault localization domain due to high localization accuracy. However, this approach generally requires costly GPS time receivers to synchronize the data at both ends, while the GPS would face satellite invisibility, atmospheric condition problems, and the installation constraint for deep underground cables. This paper proposes a zero-crossing point-based approach, where the zero-crossing point before the fault time from both ends of the cable is identified and calibrated to synchronize the measurements. With the proposed method, the measurements could be synchronized at a low cost without a GPS device. The performance of the proposed technique is evaluated via simulations of an underground cable system modeled in PSCAD, followed by a discussion on results.

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: Simulation or modeling · Consensus signal: Simulation or modeling
GenreCandidate signal: Methods · Consensus signal: none
Teacher disagreement score0.971
Threshold uncertainty score0.850

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 studies0.0010.000
Scholarly communication0.0000.001
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 head0.044
GPT teacher head0.262
Teacher spread0.217 · 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 designSimulation or modeling
Domainnot available
GenreMethods

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
Published2022
Admission routes1
Has abstractyes

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