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Record W3150964632 · doi:10.1109/pes.2007.385532

Reformulating Power Components Definitions Contained in the IEEE Standard 1459-2000 Using Discrete Wavelet Transform

2007· article· en· W3150964632 on OpenAlex
M.E. El-Hawary, Walid G. Morsi

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

VenueIEEE Power Engineering Society General Meeting · 2007
Typearticle
Languageen
FieldEngineering
TopicPower Quality and Harmonics
Canadian institutionsDalhousie University
Fundersnot available
KeywordsDiscrete wavelet transformSecond-generation wavelet transformWaveletHarmonic wavelet transformStationary wavelet transformWavelet transformWavelet packet decompositionAlgorithmComputer scienceFast wavelet transformLifting schemeFourier transformFrequency domainDiscrete Fourier transform (general)Spectral leakageMathematicsMathematical optimizationFast Fourier transformFractional Fourier transformFourier analysisArtificial intelligenceMathematical analysisComputer vision

Abstract

fetched live from OpenAlex

Summary form only given. In non-sinusoidal situations, power components definitions contained in the IEEE Standard 1459-2000 are based on a frequency-domain approach using Fourier transform (FT). The frequency-domain approach can provide amplitude-frequency spectrum while loosing time-related information. Moreover, the FT carries a heavier computational burden. To overcome these limitations, definitions of power components are reformulated in the Wavelet domain using the discrete wavelet transform (DWT). Using the DWT preserves the information concerning time and frequency and also reduces the computational time and effort by dividing the frequency spectrum into bands or levels. The results of applying the reformulated definitions show that the problem of spectral leakage between wavelet levels can be minimized by suitably choosing the wavelet family along with suitable mother wavelet. The reformulated definitions could be useful for setting tariff and evaluating the quality of the electric energy supply especially when considering non-stationary waveforms where the Fourier transform based power components definitions fail.

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)0.002
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Simulation or modeling · Consensus signal: Simulation or modeling
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.195
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.001
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 head0.035
GPT teacher head0.259
Teacher spread0.224 · 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