Improved Teager Energy Operator and Improved Chirp-Z Transform for Parameter Estimation of Voltage Flicker
Bibliographic record
Abstract
Effective estimation of voltage flicker components plays an important role in distribution systems for either flicker meters or flicker compensators. A novel approach has been presented in this paper to accurately estimate voltage flicker components by using the improved Teager energy operator (ITEO) and the improved chirp-Z transform (ICZT). The error correction factor K of the Teager energy operator is presented and ITEO is established to reduce the extraction errors of voltage flicker waveform. ICZT is used to extract the frequency and magnitude of the voltage envelope which is corrected by the K factor of ITEO. The effects of signal sampling rate, sampling number, spectrum subdivision points of ICZT, voltage harmonics and interharmonics, frequency fluctuation, and white noise are investigated. The implementation of the proposed approach in the digital-signal-processor platform is also introduced. Multiple simulation and experimental test application results validate the accuracy and efficiency of the proposed approach.
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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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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 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".