The Localization of Electrical Faults in Powerlines Using Machine Learning Methods

The objective of this study is to compare a series of numerical methods for localizing an electric fault on powerlines. The powerline considered would be simulated, for different fault cases using the software, MATLAB Simulink. Next, different methods will be used to compute the distance of the fault from the source. Finally, these results will be compared. The methods considered use different machine learning methods. In the study would be presented only the most significant results.

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Published
2025-05-14
DOI
https://doi.org/10.1109/optim-acemp62776.2025.11075265
Primary Topic
Machine Fault Diagnosis Techniques
Type
article
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article

The Localization of Electrical Faults in Powerlines Using Machine Learning Methods

Călin Munteanu, Ilieş Alin Ioan
Machine Fault Diagnosis Techniques
article

The Localization of Electrical Faults in Powerlines Using Machine Learning Methods

Călin Munteanu, Ilieş Alin Ioan
article en

Abstract

The objective of this study is to compare a series of numerical methods for localizing an electric fault on powerlines. The powerline considered would be simulated, for different fault cases using the software, MATLAB Simulink. Next, different methods will be used to compute the distance of the fault from the source. Finally, these results will be compared. The methods considered use different machine learning methods. In the study would be presented only the most significant results.

Technical University of Cluj-Napoca (RO)
Openalex Percentile: Top 80%
Machine Fault Diagnosis Techniques
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The Localization of Electrical Faults in Powerlines Using Machine Learning Methods — Călin Munteanu, Ilieş Alin Ioan · (2025) | TGRS Research Map | TGRS