Multi-Pulse Rectifier Based on an Optimal Pulse Doubling Technique
Bibliographic record
Abstract
This paper presents pulse multiplication technology based on an optimal Pulse Doubling Technique (PDT) to upgrade a 28-Pulse Rectifier (28-PR) to a 56-PR. The optimal PDT comprises a Tapped Interphase Reactor (TIPR) with a low kVA-rating and two diodes. The number of pulses can be increased from 28 to 56 using the PDT so that the input current harmonics are reasonably mitigated. Additionally, the 14-phase Polygon-Connected Autotransformer (PCA) is designed in such a way that it can be used for retrofit applications. A detailed simulation analysis in the MATLAB/Simulink environment is carried out, and the results show that the improved quality indices of the final AC input and DC output power are equivalent to the IEEE 519-2014 standard and meet sensitive industrial application requirements with an input current Total Harmonic Distortion (THD) lower than 3%. Moreover, the power factor also maintained unity for a wide operating range. The optimal PDT scheme is affordable and easy to implement as only a small-capacity PDT (only 1% of the output power) is needed to double the pulse number. An experimental prototype is developed to verify the simulation results.
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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 | 0.000 | 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 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".