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Record W3049683608 · doi:10.1109/access.2020.3015973

Partial Discharge Localization Using Electromagnetic Time Reversal: A Performance Analysis

2020· article· en· W3049683608 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

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

VenueIEEE Access · 2020
Typearticle
Languageen
FieldEngineering
TopicGeophysical Methods and Applications
Canadian institutionsnot available
FundersShahed UniversityMinistry of Science Research and TechnologyDeutscher Akademischer AustauschdienstBabol Noshirvani University of TechnologyUniversity of TorontoRWTH Aachen UniversityAmirkabir University of TechnologyNational Aeronautics and Space Administration
KeywordsMultilaterationElectromagnetic coilPartial dischargeTransformerLambdaMathematicsAlgorithmMathematical analysisElectrical engineeringComputer scienceAcousticsPhysicsVoltageGeometryOpticsEngineeringAzimuth

Abstract

fetched live from OpenAlex

In this study, first, a comparison on the application of electromagnetic time reversal (EMTR) and time difference of arrival (TDoA) in partial discharge localization in power transformers is presented. A two-dimensional finite-difference time-domain simulation is used to calculate the signal recorded by the sensors. Results show that, in a transformer tank excluding its windings, both methods yield similar results in terms of location accuracy, although the EMTR method only needs one sensor to localize the partial discharge (PD) source while the TDoA method needs at least three sensors in the 2D localization problem. However, the presence of transformer windings leads to a degradation of the performance of the TDoA method if the line of sight from the source to the sensor is blocked by any of the winding blocks. On the other hand, the presence of the transformer windings has an effect on the localization of PD sources that occur between two adjacent phase windings when the distance between the outer winding distances is shorter than the minimum wavelength, <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"> <tex-math notation="LaTeX">$\lambda _{\mathrm {min}}$ </tex-math></inline-formula> . The degradation is directly caused by the diffraction limit. It is shown that, if the distance between two adjacent phase windings is greater than <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"> <tex-math notation="LaTeX">$\lambda _{\mathrm {min}}$ </tex-math></inline-formula> , the EMTR process can locate PD sources occurring between two adjacent phase windings with acceptable accuracy. A case of occurrence of PDs in close proximity (less than <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"> <tex-math notation="LaTeX">$\lambda _{\mathrm {min}}$ </tex-math></inline-formula> /2) to a single metallic object is analyzed both numerically and experimentally. The analysis reveals that although a degradation in the accuracy of the localization is observed compared to the case of longer distances between the PD source and the metallic object, a reasonable localization error of 10 mm (corresponding to <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"> <tex-math notation="LaTeX">$\lambda _{\mathrm {min}}$ </tex-math></inline-formula> /10) is obtained.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

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)0.000
metaresearch head score (Gemma)0.000
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: Simulation or modeling
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.317
Threshold uncertainty score0.341

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
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 head0.029
GPT teacher head0.283
Teacher spread0.254 · 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