Wavelet transform as a postprocessing diagnostic tool for fault identifications of high-voltage direct current transmission system
Bibliographic record
Abstract
This short communication focuses on exploiting the inherent advantages of discrete wavelet transformation (DWT) as a diagnostic tool for post-processing and for identifying the faults that occur in the standard high-voltage direct-current (HVDC) transmission network. In particular, a set of investigations are developed and examined for single-line-to-ground fault on the generation and on the load side converter, and DC-link fault. For this purpose, a standard 12-pulse line-commutated converter (LCC)-HVDC transmission network along with the DWT algorithm is numerically modeled in the MATLAB/PLECS simulation software. Furthermore, in this paper, a set of designed faulty conditions are predicted using the output of DWT and the results of numerical simulation are presented. Results are in good agreement with expectations to prove that DWT is an effective tool for fault diagnostics.
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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".