Simulation Study of the Measurement Characteristics of Equipotential Shielding Capacitor Voltage Divider
Bibliographic record
Abstract
The online measurement of transient voltages is crucial for maintaining the reliability and safety of ac power systems. With the construction of UHV/EHV ac power systems, the voltage levels of ac equipment continue to increase, and traditional capacitor voltage dividers (CVDs) become unreliable due to the instability of their ground capacitance. This article proposes an equipotential shielding CVD (ES-CVD) and conducts simulation research on its measurement characteristics. The results show that a stable measurement can be guaranteed when the distance to the ground is greater than ten times the diameter of the measuring spherical conductor. The ES-CVD can effectively prevent the electric field strength on the surface of the measuring spherical conductor from exceeding the critical discharge field strength. The high-voltage wire to be measured and adjacent high-voltage wires have a significant impact on the ground capacitance of the measuring spherical conductor. However, the shielding electrode can significantly reduce their impact. Compared to a CVD without a shielding electrode, a divider with a shielding electrode can reduce the measurement error by one order of magnitude, which meets the measurement requirements of transient voltage. The research results in this article can provide a reference for measuring high-voltage ac transient voltage.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".