Spectral Analysis of Electrical Discharge in Mineral Oil—Comparison With Air Discharge
Bibliographic record
Abstract
This study aims to compare the spectral characteristics of electrical discharges in mineral oil (MO) with those in air. The results demonstrate that electrical discharge channels in MO exhibit a resistive nature, as evidenced by the phase difference, and that discharges in this medium are associated with higher energy levels due to their superior dielectric strength. This necessitates higher voltages for discharge initiation compared to electrical discharges in air, which involve lower energy levels due to air’s lower dielectric properties. Temporal domain analysis shows that electrical discharges in air propagate faster than those in MO. In addition, fast Fourier transform (FFT) analysis reveals that air discharges exhibit a broader spectrum with more high-frequency components, indicating faster propagation than MO discharges. The differences in dielectric properties—such as dielectric strength, breakdown voltage, density, and viscosity—are lower in the air than in MO, significantly influencing discharge characteristics, including current, voltage, power, and energy. These findings offer crucial insights into the nature of discharge channels, energy levels, propagation speeds, and discharge dynamics in air and MO. This contributes to developing more effective insulation monitoring and predictive maintenance strategies in electrical power systems.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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) | 0.001 | 0.000 |
| Bibliometrics | 0.002 | 0.006 |
| 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".