Comparative analysis of the method of insulation condition monitoring by ultraviolet radiation of surface partial discharges
Bibliographic record
Abstract
Relevance. Unreasonable overhead power line outages are typically associated with flashover of line insulation due to contamination and moisture. Partial discharges on the insulation surface are fairly reliable indicators of dangerous levels of contamination and can be detected in a variety of ways. Remote non-invasive methods have become more popular for preventive control of the characteristics of surface partial discharges (SPD), they are based on the registration of acoustic and electromagnetic signals of various partial frequency ranges, as well as optical radiation in the infrared (IR) and ultraviolet (UV) parts of the spectrum. Daytime UV flaw detectors are considered promising for the realization of UV-inspection, they are also known by other names: UV cameras, UV visualizers, UV scanners, etc. These devices register corona radiation and surface partial discharges in the range of 240-280 nm and can be used in the daytime due to light filters cutting off solar radiation. Currently clear relationships between the characteristics of discharge processes and the degree of contamination of the insulation and its moisture-discharge characteristics have not been obtained even in laboratory studies. Of course, the complexity of the processes plays a determining role in that, but insufficient knowledge of the properties of the equipment and the influence of external factors contribute on the UV-inspection results. Purpose. To investigate the transmission characteristics of several types of UV flaw detectors and to evaluate the influence of the propagation ambience on UV-inspection results. Restrictions on the range of equipment settings and on the conditions for conducting UV-inspection in the field should be formulated based on the research results. Methods. Experimental research methods were used both in laboratory conditions and in the process of UV-inspection of real objects to solve the tasks. Results. Relationships between the readings of the photon counter and the area of UV-radiation from the input gain of UV flaw detectors have been experimentally established. Double impact of the effect of water vapors and dust particles on the result of recording the intensity of discharges was revealed. The practical application of the obtained results in ultraviolet inspection makes it possible to improve the diagnostic process, thereby increasing the reliability of electrical devices.
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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 | 0.002 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 0.001 |
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".