On the Implementation of Time-frequency Transforms for Defining Power Components in Non-sinusoidal Situations: A Survey
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Bibliographic record
Abstract
Abstract Power quality indices play an important role in decision making in deregulated competitive environments. Useful power quality indices require clear and accepted definitions of power components as well as the RMS values of voltage and current. This is especially true in case of non-stationary distorted waveforms, where neither a frequency-domain–based approach using fast Fourier transform tools nor a time-domain–based approach using real-time data give satisfactory results. Wavelet transform is able to represent any distorted waveform in a time-frequency spectrum while preserving relevant information in both time and frequency domains. Different methods have been proposed in an attempt to define power components in the wavelet domain. This article offers a critical evaluation of the current state-of-the-art concerning this topic. The article also offers conclusions and suggested future work.
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Full frame distilled prediction
Teacher imitationNot 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.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it