Average value modeling of six‐pulse diode rectifier considering unbalance conditions in supply voltage and impedance
Bibliographic record
Abstract
Diode rectifiers are widely used in many applications, and therefore, there is a need for an accurate model to study the rectifiers. Because of the complexity and time consuming of the analytical model of rectifiers, the average value modeling has been introduced. This paper proposes a novel average value model (AVM) for the line-commutated rectifier bridge supplied with an unbalanced power source. The unbalance condition, here, refers to the asymmetry of the three-phase voltage magnitude and the three-phase impedance, which is possible due to the occurrence of asymmetry in the sources with winding such as power sources, generators, and transformers. According to the three-phase input current of the rectifier, one cycle is divided into some intervals, and the differential equation for each interval is provided. Then, utilizing these equations, the average value of the derivative of the load current is derived from which the average value of the load current and voltage can be calculated. The proposed AVM is then verified using simulation and experimental results for the diode rectifier bridge with the load of the brushless synchronous generator field winding. Besides, the model is investigated for different load and supply parameters.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.000 | 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".