Addressing IEC Flickermeter Deficiencies by Digital Filtration Inside a Sliding Window
Bibliographic record
Abstract
Although globally deployed for flicker assessment, the flickermeter presented by International Electrotechnical Commission (IEC) Standard 61000-4-15 has been proved to suffer from some deficiencies regarding voltage rectangular modulation and interharmonics. The latter results in flickermeter inability to accurately measure flicker for non-incandescent lamps, which are ubiquitous nowadays. The flickermeter inaccuracies tend to arise from its demodulator. So far, few solutions have been provided. Furthermore, the existing solutions deal with only the interharmonic case. This paper introduces a method to address IEC flickermeter deficiencies by developing a digital signal processing block that demodulates the voltage in a real-time manner for voltages that include interharmonics or are affected by rectangular modulation. The suggested demodulator implements discrete Fourier transform inside a sliding window. For rectangular modulation, this approach is used to demodulate the voltage. Meanwhile, for the interharmonics problem, this approach provides the interharmonic frequency. Using the measured frequency, least error squares technique is then employed inside another sliding window to find the interharmonics amplitude. On this basis, a modified flickermeter is devised. Performance of the modified flickermeter is evaluated and its effectiveness is verified using the results obtained from an experimental set-up. The contribution of this paper is not limited to IEC flickermeter modification; the proposed method can be employed for any application requiring interharmonic measurement.
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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) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 0.001 |
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".