Technical Development of the IEEE Guide for Visual Corona Testing of Insulator Assemblies and Line Hardware and its Application in the Testing of 765-kV Transmission Line Insulator Assemblies
Bibliographic record
Abstract
Traditionally corona testing has been performed in laboratories by mounting a single phase mock-up of the conductor/hardware/insulator assembly at a given height above the ground and applying 110% of the rated line-to-ground operating voltage. If the test setup is shown to be free of corona by this test, then it is considered that the assembly will be free of corona under operating conditions. This method does not appear in any standards, but is used as a generally accepted test method. In spite of its general acceptance, this test method can give erroneous results. This is due to the fact that the inception of corona occurs at a given electric field gradient rather than a given absolute voltage. Under actual operating conditions, the electric field gradient at the conductor/hardware/insulator assembly is a function of phase spacing, the local geometry, and the applied 3-phase voltage. In order to correctly perform such a test in a laboratory, it is essential that the maximum gradients occurring on the conductors in the field be reproduced in the laboratory test. To address this shortcoming in test procedures, the IEEE PES Transmission and Distribution Committee's Lightning and insulator and corona and field effects working groups are engaged in the development of a guide for the performance of visual corona and RIV testing on insulator assemblies and line hardware.This paper describes the theoretical and experimental background upon which the technical development of the guide is based, and the application of the procedures in the guide as used in testing insulator assemblies and hardware for a new design 6-conductor bundle 765 kV transmission system.
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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 | 0.003 | 0.005 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.004 | 0.002 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.003 | 0.001 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.018 | 0.028 |
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".