Influence of Trace Impurities from SF_6 New Gas on the Life of SF_6-insulating Electrical Equipment
Bibliographic record
Abstract
In order to provide references for quality control of new SF6 gas in electrical equipment,the influence of trace impurities in new SF6 gases on SF6-insulating electrical equipment was experimentally investigated.An internal default as metal point discharge on the center rod was simulated by using a straight-line isolator installment which shared gas chamber with a current transformer.Then experiments of using SF6 new gas with various qualities under 2 voltage modes,single 220 kV single voltage mode and 220 kV/3 150 A synchronous upward current-voltage mode,were performed for about 100 h.In the experiments,variations of volume concentration of each impurity in the SF6 gases were detected by a gas chromatography mass spectrometry analyzer and a DPD SF6 impurity analyzer(made in Canada).The results show that,more by-products like SO2F2,SOF2,and SO2 will be generated when electrical equipment is filled with new SF6 gas which has mass trace impurities,including fluorinated alkane,fluorizating sulfonyl,and carbon sulfur fluoride;considering the corrosive effect of SO2 on the equipment,it is concluded that when SF6 is filled with new gas with high level impurities,the life of electrical equipment will be shortened,especially that of breaks will be shortened.
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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 | 0.001 |
| 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".