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Evaluation of Electrical Tree Length Information Based on Partial Discharge Signal

2025· article· en· W4413513815 on OpenAlex

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fundA Canadian funder is recorded on the work.
no affNo Canadian affiliation: this work is invisible to an affiliation-only frame.
No Canadian affiliation. An affiliation-only frame, the usual design, would never have seen this work. It is one of the works that make the case for inverting the frame.

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldComputer Science
TopicAdvanced Decision-Making Techniques
Canadian institutionsnot available
FundersCanadian Society of Petroleum Geologists
KeywordsPartial dischargeComputer scienceTree (set theory)SIGNAL (programming language)Electrical engineeringMathematicsVoltageEngineeringProgramming language

Abstract

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Electrical treeing is a common phenomenon associated with insulation degradation. When these trees extend to the ground side, cable breakdown occurs. To ensure safe transmission in power systems, it is crucial to quantify the growth length of electrical trees using specific indicators. However, existing PRPD spectra exhibit limited capability in characterizing the length of electrical branches, as phase parameters become indistinguishable under varying branch lengths. Currently, the most widely used methods for characterizing partial discharge phenomena are the T-F map and PRPD diagrams. According to experimental results, the <tex xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">$T-F$</tex> map did not show significant differences as the electrical tree grew. In the experiment, the PRPD diagrams only exhibited amplitude variations, which were heavily influenced by voltage levels. Therefore, these methods were deemed unsuitable for accurately characterizing electrical tree growth. Given that the growth of electrical trees exhibits chaotic characteristics, this study integrates both nonlinear and linear quantities in partial discharge analysis to identify differences in partial discharge behavior at various growth stages. In this study, after normalizing the original partial discharge signal, amplitude information and sign information were extracted. The amplitude information was treated as a nonlinear quantity, while the sign information was considered a linear quantity. Both were computed using the DFA algorithm and subsequently plotted on a graph, with the amplitude information represented on the <tex xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">$\boldsymbol{x}$</tex>-axis and the sign information on the <tex xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">$y$</tex>-axis. The results indicate that as the electrical tree progresses, the data tend to migrate towards the upper-left quadrant. The experimental results demonstrate that this method can, to some extent, determine the growth of electrical trees by measuring partial discharge signals during their growth process.

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Full frame distilled prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Simulation or modeling · Consensus signal: none
GenreCandidate signal: Methods · Consensus signal: none
Teacher disagreement score0.906
Threshold uncertainty score0.263

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0000.001
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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.

Opus teacher head0.023
GPT teacher head0.331
Teacher spread0.308 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

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Citations0
Published2025
Admission routes1
Has abstractyes

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