A New Technique to Detect Faults in De-Energized Distribution Feeders—Part I: Scheme and Asymmetrical Fault Detection
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Bibliographic record
Abstract
Re-energizing an overhead distribution feeder safely is a major consideration for a utility's safe work practice. One way to improve the safety is to determine whether the feeder still experiences short circuits before it is energized. In this paper, a novel fault detection technique is proposed to detect if a de-energized distribution system still experiences short-circuit faults. The proposed method involves injecting a thyristor-generated-controllable signal into the de-energized feeder. The feeder voltage and current responses are analyzed to determine if a fault still exists. A thyristor gating control strategy and fault detection algorithm are also developed in this paper to detect all possible types of faults that can occur in a system. The effectiveness of the proposed method has been verified through theoretical analysis, computer simulations, and lab tests.
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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 | 0.001 | 0.001 |
| 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 it