Bibliographic record
Abstract
The objective of this thesis research is to develop an efficient method for accurate detections of power line harmonic distortions for the control of active filters. The research has achieved its objective with four significant results. First, an adaptive power line harmonic detection method is developed, which is based on the findings of extensive research in the areas of inside and outside of power electronics controls. Second, a simple and practical formulation of the adaptive harmonic detection method is developed, which is simplified significantly from the original complex design formulations for noise cancellations. Third, vigorous verifications of effectiveness of the adaptive detection method using computer simulations are carried out, which cover the steady state operations, the dynamic operations, normal power line conditions, non-ideal supply and load conditions, etc. Fourth, experimental verifications of the accuracy of the adaptive detection method are conducted, which cover typical distorted power line conditions for normal and unbalanced operations. For illustration, this thesis presents carefully designed computer simulation and experimental case studies that cover a wide range of power line conditions.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| 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 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".