Bibliographic record
Abstract
This paper presents a noninvasive method of measuring three-phase currents using magnetic sensors that can be used for continuous monitoring, automation, and protection of power grids. The non-intrusive nature of these sensors gives operational and economic benefits in installing them at the existing distributed generation sites, and power substations. These sensors are linear in operation, free of saturation, and need minimum-duration or no outage for installation as compared to the conventional current transformers. The paper describes magnetic field simulation, calibration, and experimental validation of magnetic sensors for accurate measurement of three-phase currents. Laboratory experiment results of three-phase low current measurements for two types of overhead structures: triangular and horizontal are rendered as a validation of the proposition. The performance verification of these sensors is further achieved by conducting field experiments for measuring currents up to 1500A. The sensors yield promising results with a maximum error of 1.15% in estimation of three-phase currents. The magnetic sensors showed a satisfactory performance in accurately reproducing current waveforms consisting of fundamental frequency and harmonics that are typically present in modern power grids.
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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) | 0.001 | 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 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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".