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Record W2115505816 · doi:10.1109/pesc.2007.4342149

Implementation of the Wiener Filter for Extracting Power Quality Disturbances

2007· article· en· W2115505816 on OpenAlexaff
A. Elnady, Aboelmagd Noureldin, Yan‐Fei Liu

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldEngineering
TopicPower Quality and Harmonics
Canadian institutionsRoyal Military College of CanadaQueen's University
Fundersnot available
KeywordsWiener filterComputer scienceFilter (signal processing)Modular designControl theory (sociology)Time domainFrequency domainState spaceTracking (education)Electronic engineeringAlgorithmArtificial intelligenceEngineeringMathematicsComputer vision

Abstract

fetched live from OpenAlex

This paper introduces a novel modular strategy for real time extraction of the current and voltage disturbances. The main advantage of this technique is that it does not have mathematical complexity and does not require any model or state-space formulation to extract the disturbances like the other commonly used state-space techniques. In addition, it is very simple for practical and real time implementation if compared to the existing time-domain and frequency-domain methods. The proposed technique is based on the Wiener filter designed adaptively by using a sliding windowing procedure. This Wiener filter is employed to design a generalized extraction strategy for tracking and extracting the most common power quality disturbances. Digital simulation results on the most common power quality problems are demonstrated to validate the proposed strategy.

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)0.001
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: Empirical
Teacher disagreement score0.329
Threshold uncertainty score0.139

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
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 head0.042
GPT teacher head0.351
Teacher spread0.309 · 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

Citations2
Published2007
Admission routes1
Has abstractyes

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