Comparative measurements of two partial discharge measurements used for form wound coils/bars as quality assurance tests
Bibliographic record
Abstract
Several utilities both in Canada and in the USA have been using commercial on-line partial discharge (PD) systems as on-line monitoring tools. Partial discharge tests have been used historically to characterize bars/coils that have been sent to Powertech Laboratories for voltage endurance and thermal cycling tests so that the bars that displayed the highest PD quantities were subjected to voltage endurance tests. Utilities are now beginning to specify the limits for PD magnitudes and other related PD quantities as a quality assurance measure in their technical specifications for large motors and hydrogenerators. There appears to be confusion as to what are the reasonable limits for these quantities and whether or not these limits make practical sense. Since Powertech has had the unique opportunity to examine several insulation designs over the last decade this paper is an early attempt to document the current levels of PD quantities that are being measured on bars/coils being manufactured with modern insulation systems. No attempt has been made to correlate these quantities with its performance on voltage endurance (VE) test times but this work is ongoing. Several bars from different manufacturers were subjected to PD measurements at their normal line-to-ground voltage. These PD measurements were made using Powertech's classical PD system as well as a commercial system. One significant difference was that the PHA system uses pico-coulomb to represent charge magnitude while PDA system uses millivolt. Laboratory calibration was done to correlate these discharge magnitudes. Results showed that if the discharge magnitudes and the number of PD pulses were small both the classical and the commercial system gave similar PD responses. On the other hand if the discharge rate (number of pulses per second) was large the classical PD measurement system tended to saturate. Historically, when such saturation occurred during measurements with the classical PD system, measurements were repeated at a lower test voltage (for example 0.8 pu). Subsequent dissections of samples that exhibited such high PD showed the presence of a large number of voids in the groundwall insulation.
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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 | 0.006 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| 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".