Realization of transformer winding network from sweep frequency response data
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
Sweep Frequency Response analysis (SFRA) is a widely used technique for condition assessment of power transformers and reactors. With SFRA, it is possible to analyze the integrity of transformer without prior dismantling. Changes in geometric configuration change the impedance of network which in turn changes the transfer function. Changes in transfer function will reveal a wide range of failure modes. SFRA allows the detection of changes in transfer function of individual windings within transformers and reactors and indicate movement or distortion in core and windings of the transformer. The RLC network can be identified by its frequency dependent transfer function. In order to create a framework to facilitate assisted interpretation algorithms, SFRA curves are parameterized. The simplest and most useful mechanism is the reduction of the curves to pole-zero representation. SFRA traces are characterized by having many undulations and extending over a wide dynamic range on both axes. This can make accurate pole-zero representation a challenge. In this paper an attempt has been made to realize the electrical network from the SFRA response data of a high voltage reactor.
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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 | 0.000 |
| 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 it