Real-time testing of Newton-phaselet method for calculating the power factor of single phase loads
Bibliographic record
Abstract
A combination of Newton iterations and phaselet tight frames allows calculating the power factor of a single phase load. In this paper, the real-time implementation and experimental testing of the Newton-phaselet method are presented. The tested method is structured to employ the Newton iterations in order to estimate values for the apparent power S, and to utilize phaselet tight frames to calculate an angle v for the estimated S at each iteration. The estimated S and calculated v at each iteration provide a numerical value for the active power P. This calculated value of P is compared to the measured one in order to determine the required adjustment in S for the next iteration. The Newton-phaselet method is implemented in real time by using a digital signal processing board, where the measured active power is fed as the input. Experimental performances of the Newton-phaselet method are investigated for single phase linear, non-linear, and inverter-fed loads supplied at different frequencies. Test results demonstrate high accuracy, simple implementation, low memory requirements, fast convergence, and negligible sensitivities to harmonic components and supply frequencies.
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How this classification was reachedexpand
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 | 0.000 | 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 itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, 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".