Electromagnetic Wave Applications for Reliable Fault Detection in Power Transformer Windings

This paper presents a novel approach for the localization of radial faults in power transformer windings using electromagnetic waves, emphasizing the critical issues of reliability and noise. The proposed analytical method aims to enhance the reliability of power transformers by effectively identifying and diagnosing radial deformations. The study utilizes matched filtering techniques to analyze received signals, ensuring improved accuracy despite environmental noise interference. By comparing the reference signals from healthy transformers with those from faulty conditions, the methodology demonstrates a robust framework for real-time monitoring. The findings indicate that addressing noise and reliability significantly contributes to the effectiveness of fault detection systems in power transformers.

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Published
2024-11-20
DOI
https://doi.org/10.1109/icsrs63046.2024.10927471
Primary Topic
Power Systems Fault Detection
Type
article
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article

Electromagnetic Wave Applications for Reliable Fault Detection in Power Transformer Windings

Hesam Rahbarimagham, Gevork B. Gharehpetian, Sina Beydaghi, Sevda Beydaghi
Power Systems Fault Detection
article

Electromagnetic Wave Applications for Reliable Fault Detection in Power Transformer Windings

Hesam Rahbarimagham, Gevork B. Gharehpetian, Sina Beydaghi, Sevda Beydaghi
article en

Abstract

This paper presents a novel approach for the localization of radial faults in power transformer windings using electromagnetic waves, emphasizing the critical issues of reliability and noise. The proposed analytical method aims to enhance the reliability of power transformers by effectively identifying and diagnosing radial deformations. The study utilizes matched filtering techniques to analyze received signals, ensuring improved accuracy despite environmental noise interference. By comparing the reference signals from healthy transformers with those from faulty conditions, the methodology demonstrates a robust framework for real-time monitoring. The findings indicate that addressing noise and reliability significantly contributes to the effectiveness of fault detection systems in power transformers.

Islamic Azad University, Tehran (IR), Amirkabir University of Technology (IR), Alzahra University (IR), Rafsanjan University of Medical Sciences (IR)
Affordable and clean energy
Openalex Percentile: Top 64%
Power Systems Fault Detection
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Electromagnetic Wave Applications for Reliable Fault Detection in Power Transformer Windings — Hesam Rahbarimagham, Gevork B. Gharehpetian, et al. · (2024) | TGRS Research Map | TGRS