Probabilistic Models of Harmonic Currents Produced by Twelve-Pulse AC/DC Converters
Bibliographic record
Abstract
The probabilistic approach is an efficient mean for harmonic prediction since it allows to take into account the randomly varying operating conditions of static converters. Although the six-pulse ac/dc converter has been the subject of probabilistic modeling, little consideration has been given to the 12-pulse ac/dc converter. In high-power applications, such as large rated dc power supplies and large rated dc and ac drives, 12-pulse ac/dc converters are usually preferred since they allow to reduce system disturbances due to harmonic currents. This paper presents an analysis of the random properties of harmonic currents produced by 12-pulse ac/dc converters that operate under random variations of their dc load and voltage unbalance. The probability density functions of the amplitudes and phase angles of the harmonic currents (of orders 12 k/spl plusmn/1 and 12 k-6/spl plusmn/1) are established and validated by results obtained from Monte Carlo simulations.
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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 | 0.005 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| 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 | 0.000 |
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".