The effects of salt contamination deposition on HV insulators under environmental stresses
Bibliographic record
Abstract
This paper examines the issue of salt contamination accumulation, flow of leakage current and surface flashover on high voltage insulators. Artificial contaminants were prepared using NaCl and distilled water. With long-term accumulation of salt particles on high voltage insulators in the presence of wind, ambient temperature, humidity, fog and moisture, conducting layers is formed on insulators' surface. This conductive layer provides an ideal path for leakage current to flow from the high voltage conductor to the grounded side of the insulators. Insulators' layer moistened and heated due to environmental stresses which cause an increase in leakage current and dry bands formation. Partial arcs can occur across the dry bands. Under favourable conditions a complete flashover might occur. The performance of the polluted insulators mainly depends on the conductivity of the polluted surface layer or on the equivalent salt deposited density of the polluted surface layer, which are affected by environmental conditions. Insulator is tested with different conductivities in a series of experiments including ESDD and NSDD measurement. COMSOL Multiphysics software is used to simulate and determine the electric field and potential distribution as well as the resulting leakage current flow on its polluted surface. The measurement results have been compared with the COMSOL results and found to be in good agreement. Outcomes will lead to the modelling of insulators and electric field response of insulators under different conductivities and environmental stresses.
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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 | 0.000 |
| 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) | 0.001 | 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".