A novel double-ended fault location identification scheme for multi-terminal HVDC grids based on Hilbert-Huang transform
Bibliographic record
Abstract
Accurate identification of fault location in multi-terminal HVDC grids contributes to reducing the downtime of the faulted segment and determining critical locations frequently exposed to fault incidents. A double-ended fault location identification scheme for multi-terminal HVDC grids is proposed in this paper based on Hilbert-Huang Transform (HHT). First, HHT is utilized to extract the instantaneous frequency and energy from voltage measurements. Then, a setting-less criterion based on outlier detection is employed to capture the arrival time of the initial fault-induced backward traveling waves. Based on the arrival instants at line terminals, the fault location is identified with high precision. The proposed scheme can locate high-resistance faults up to 1000 Ω within 1 ms. Various simulations are executed to demonstrate the accuracy and reliability of the proposed scheme.
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How this classification was reachedexpand
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 itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, 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".