Bubbling Inception Temperature in Power Transformers—Part 1: Comparative Study of Kraft Paper, Thermally Upgraded Kraft Paper, and Aramid Paper With Mineral Oil
Why this work is in the frame
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Bibliographic record
Abstract
The bubbling inception temperature (BIT) of insulating materials used in transformers is critical for their performance and lifespan. This study, which represents the first part of a two-part series, provides a comparative analysis of the BIT for kraft paper, thermally upgraded kraft paper (TUK), and aramid paper impregnated with mineral oil. A customized experimental setup was used to measure the BIT under controlled laboratory conditions. The uniqueness of the setup lies in its precise control of dynamic load conditions via an autotransformer, real-time bubble detection, continuous moisture in oil and temperature monitoring using sensors, the use of capacitive measurement to assess moisture content in paper, and the flexibility to test different oils and insulation materials. This combination enables accurate analysis of bubble formation in oil-paper insulation systems under realistic conditions. Results show that TUK paper has the highest BIT, followed by kraft and aramid papers. Additionally, the study introduces new empirical equations for predicting BIT based on water content for each paper type, notably filling a gap for aramid paper. These equations are valuable for practical engineering applications. The research underscores the importance of moisture control in determining BIT and suggests future studies focused on standardizing methodologies and exploring different dielectric fluids. The findings contribute to improving the design, maintenance, and reliability of transformer insulation systems. Part 2 of this study further explores the long-term effects of thermal aging and alternative dielectric fluids on BIT.
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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 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| 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 it