Temporal and spatial characteristics of soluble salt components accreted on the insulator surface
Bibliographic record
Abstract
Due to the differences in typical pollution sources, the soluble salt composition deposited on the naturally contaminated insulators varies with the region. As different soluble salts have different effects on the pollution flashover voltage of insulators, it is necessary to investigate the spatial and temporal distribution of the soluble salt composition deposited on the insulator surface to make the external insulation design more scientifically and reasonably. In this study, an artificial contamination test platform was built to collect the contamination naturally deposited on the specimens. The test results showed that the contamination composition deposited on the specimen was similar to that in the atmosphere, and the inclination angle of the specimen and the duration of pollution deposition had little influence on the contamination composition. After examining the industrial post insulators from actual substations, it was found that the contamination composition was almost the same for different insulator surface materials, insulator shed types, and voltage polarities. It was also found that the deposited contamination was mostly influenced by pollution sources. The results can provide a reference for the studies of pollution distribution of natural insulators.
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 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 | 0.001 | 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) | 0.002 | 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".