Computer based on-line diagnostics of insulation quality of high voltage apparatus
Bibliographic record
Abstract
The safe and reliable operation of a power system is directly related to the insulation condition of high voltage apparatus in service, which may age and deteriorate under normal operating conditions. Therefore, the detection of insulation quality of high voltage apparatus is important. This task can be implemented advantageously by the measurement of dissipation factor and capacitance using on-line digital methods, since these methods require no service interruption thus resulting in low labor cost. Moreover, on-line measurements under operating voltage are more helpful in the assessment of the status of the insulation. In this work, a computer-aided system for on-line monitoring dissipation factor and capacitance was developed based on a method, which employs the Discrete Fourier Transform (DFT). The DFT is performed on the scaled down analog voltage and current signals obtained using a Digital Storage Oscilloscope (DSO) board, and results are displayed using the graphic user interface which is implemented with software Labview. To optimize system performance, software simulation and laboratory tests were carried out. Based on the results, optimal values of measurement parameters have been suggested. Field tests were conducted at Manitoba Hydro's Dorsey station to evaluate the insulation of a 230KV current transformer unit using the developed system.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| 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) | 0.000 | 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 teacher head, 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".