Research and Design of Power Transformer Online Monitoring System
Bibliographic record
Abstract
As the most important equipment in the power grid, the safe and reliable operation of the power transformer is of great significance to ensure the stability of the power system. On-line monitoring of power transformers can ensure the safe and stable operation of transformers. This paper introduces an on-line monitoring system for temperature, vibration and internal video information of power transformer. The system is allowed to be applied under harsh industrial conditions. This paper describes the design of the system in detail, including the realization of hardware and software. Finally, an example of field test and simple reliability analysis are given to confirm its reliability and function in transformer on-line monitoring. The system can monitor the running state of the transformer, so that the monitoring personnel can find the abnormal and hidden faults of the transformer in time. This can not only prevent the occurrence of sudden accidents of the transformer, but also carry out the maintenance of the transformer without power outage, prolong its operating life, and improve the reliability, safety and economy of the power grid operation.
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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 | 0.001 | 0.000 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.005 | 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".