Characteristics of induced discharge on a polymer insulator surface under electro-wetting conditions
Bibliographic record
Abstract
In this paper, laboratory experiments were conducted to investigate the precipitation characteristics and induced surface discharge on polymer insulator specimens under electro-wetting conditions simulated by artificial fog-wetting conditions at different operating voltages. Based on image processing methods, quantitative analysis was carried out on precipitation parameters to obtain the deposited amount, relative distribution area, statistics of droplet size distribution and distributed droplet box dimension in relation with the duration of precipitations and operating voltages. Also, the onset voltage of surface discharge and flashover voltage were measured for the purpose of establishing the influence of the obtained precipitation parameters on the surface discharge. It was found that the precipitation process is in a dynamic balance between fog deposition and droplet evaporation, and is significantly affected by the type and level of operating voltage. Operating voltage increase results in a relatively lower deposit amount and distributing area of water droplets. There are further reduced when the precipitating duration is increased at higher voltage level. The smallsize (<; 1 mm) droplets are dominating on the specimen surface for all the investigated conditions. The large-size (> 2 mm) droplets increase with increasing AC operating voltage, but do not appear significantly under high ±DC operating voltage. When precipitation duration is increased, box dimension of droplet distribution under nonand low- operating voltage shows tendency to increase, but tendency to decrease under high operating voltage. Finally, a relationship between the onset voltage of surface discharge, the flashover voltage and the droplet distribution parameters was established, showing that the increasing precipitation regularity of water droplets on the polymer insulator specimen surface can induce more likely occurrence of surface discharge, even flashover.
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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 | 0.002 |
| 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".