Reformulating Power Components Definitions Contained in the IEEE Standard 1459–2000 Using Discrete Wavelet Transform
Bibliographic record
Abstract
In nonsinusoidal 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 nonstationary waveforms where the Fourier transform-based power components definitions fail.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot 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.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.004 | 0.010 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.003 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.003 | 0.003 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.002 | 0.002 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".