Robust and frequency-adaptive measurement of peak value
Bibliographic record
Abstract
A new approach for measuring the peak value of the fundamental component of a distorted sinusoidal signal, for power system applications, is presented. The method is applicable to single-phase as well as three-phase systems. While maintaining structural simplicity, the proposed approach is highly robust with respect to noise and distortion due to disturbances and unbalanced conditions of the system. The method is also highly tolerant of uncertainties in the setting of its internal parameters. The salient feature of the proposed approach is its capability of adapting to the variations in the center frequency of the input signal. The method is suitable for environments that frequency excursions are experienced and conventional DFT-based methods do not provide satisfactory results. Speed and accuracy of the response can also be controlled. Structural simplicity and robustness of the proposed scheme make it well suited for digital implementation on software and hardware platforms. Performance of the proposed method is presented based on simulation studies in the MATLAB environment and an experimental setup.
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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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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".