Performance of low distortion 3-phase diode rectifiers using resonant harmonic correction networks
Bibliographic record
Abstract
Resonant harmonic correction networks are presented that lower the line current harmonic distortion of three-phase diode rectifiers using a capacitor smoothed DC rail. The basic harmonic correction network consists of line inductors and capacitors connected in parallel with the rectifier. This structure injects resonant current into the AC supply that makes the line current waveshape more sinusoidal. Several modifications can be made to this basic structure that improves the rectifier performance and lowers the size of the line inductors. A twelve-pulse rectifier configuration can be used to achieve a line current distortion less than 5% using line inductors rated at around 0.14 p.u. Thyristor networks can be used to improve the rectifier power factor over a wide load range. Split resonant inductors with an IGBT switch can be used to decrease the size of the line inductors and to regulate the output DC-rail voltage over a wide load range and as compensation for fluctuating supply voltages. Experimental and simulated based performance analysis is presented that uses a per-unit system for the resonant impedance and resonant frequency.
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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 | 0.000 | 0.000 |
| 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) | 0.004 | 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".