Detection of Incipient Faults in Distribution Underground Cables
Bibliographic record
Abstract
The incipient faults in underground cables are largely caused by voids in cable insulations or defects in splices or other accessories. This type of fault would repeatedly occur and subsequently develop to a permanent fault sooner or later after its first occurrence. Two algorithms are presented to detect and classify the incipient faults in underground cables at the distribution voltage levels. Based on the methodology of wavelet analysis, one algorithm is to detect the fault-induced transients, and therefore identify the incipient faults. Based on the analysis of the superimposed fault current and negative sequence current in the time domain, the other algorithm is particularly suitable to detect the single-line-to-ground (SLG) incipient faults, which are mostly occurring in underground cables. Both methods are designed to be applied in real systems. Hence, to verify the effectiveness and functionalities of the proposed schemes, different fault conditions, various system configurations, and real field cases are examined and other transients caused by permanent fault, capacitor switching, load changing, etc., are studied as well.
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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 | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 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 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".