Identification of physical parameters of a synchronous generator from on-line measurements
Bibliographic record
Abstract
Summary form only given. A new method to determine physical parameters of a synchronous generator based on an online measurement of the electrical power, terminal voltage and field voltage, following a small perturbation of the field voltage, and the rotor angle at the same steady state operating condition is described in this paper. A multivariable linear transfer function, identified using the sampled input-output data, is converted to the parameters of the Heffron-Phillips model. Using the relations of the Heffron-Phillips parameters with the physical parameters, the physical parameters are estimated. These estimated parameters are then used in a nonlinear structure to model the synchronous generator. Experimental results with the proposed method applied to a micro-machine show good accuracy of the model and also show that the identified nonlinear model is valid at other operating conditions. At dramatically different operating conditions, however, to include the effects of unstructured nonlinearities such as magnetic saturation, the parameters of the nonlinear structure can be slightly adjusted for a better performance.
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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) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.010 | 0.004 |
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".