Details
Original language | English |
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Title of host publication | 2024 10th International Conference on Condition Monitoring and Diagnosis, CMD 2024 |
Publisher | Institute of Electrical and Electronics Engineers Inc. |
Pages | 13-16 |
Number of pages | 4 |
ISBN (electronic) | 9788986510225 |
ISBN (print) | 979-8-3503-5387-7 |
Publication status | Published - 20 Oct 2024 |
Event | 10th International Conference on Condition Monitoring and Diagnosis, CMD 2024 - Gangneung, Korea, Republic of Duration: 20 Oct 2024 → 24 Oct 2024 |
Publication series
Name | International Conference on Condition Monitoring and Diagnosis |
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ISSN (Print) | 2374-0167 |
ISSN (electronic) | 2644-271X |
Abstract
Advanced monitoring systems that combine PD detection with other methods, such as oil monitoring, increase reliability and provide operators with more accurate health assessments. This article studies the electromagnetic (EM) waves emitted from partial discharges in the ultra-high frequency (UHF) range using a special UHF sensor for integration purposes. Given the complex structure of power transformers, diagnosing partial discharges using UHF methods presents several challenges. This study addresses the impact of the transformer tank and other parameters on the impedance matching, and radiation pattern, aiming to enhance the sensitivity of the studied UHF PD sensor. A practical method for selecting the optimal frequency range for PD detection is proposed to improve the effectiveness of the UHF method and enhance the signal-to-noise ratio using frequency spectrum analysis. The results were validated by correlating the phase-resolved partial discharge (PRPD) patterns obtained through the IEC 60270 method with those from both a commercial sensor and the UHF PD sensor studied in this article. This validation confirms the effectiveness of the proposed approach in improving PD detection in power transformers.
Keywords
- Partial discharge detection, Power transformer diagnostics, Signal-to-noise ratio enhancement, UHF PD measurement, UHF PD PRPD pattern
ASJC Scopus subject areas
- Engineering(all)
- Electrical and Electronic Engineering
- Materials Science(all)
- Electronic, Optical and Magnetic Materials
- Engineering(all)
- Safety, Risk, Reliability and Quality
Cite this
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2024 10th International Conference on Condition Monitoring and Diagnosis, CMD 2024. Institute of Electrical and Electronics Engineers Inc., 2024. p. 13-16 (International Conference on Condition Monitoring and Diagnosis).
Research output: Chapter in book/report/conference proceeding › Conference contribution › Research › peer review
}
TY - GEN
T1 - Improving Sensitivity and Detection Frequency of Special UHF Partial Discharge Sensors for Power Transformer Monitoring Systems
AU - Balali, Behnam
AU - Kuhnke, Moritz
AU - Zidny, Irfan
AU - Werle, Peter
AU - Akbari, Asghar
N1 - Publisher Copyright: © 2024 The Korean Institute of Electrical Engineers (KIEE).
PY - 2024/10/20
Y1 - 2024/10/20
N2 - Advanced monitoring systems that combine PD detection with other methods, such as oil monitoring, increase reliability and provide operators with more accurate health assessments. This article studies the electromagnetic (EM) waves emitted from partial discharges in the ultra-high frequency (UHF) range using a special UHF sensor for integration purposes. Given the complex structure of power transformers, diagnosing partial discharges using UHF methods presents several challenges. This study addresses the impact of the transformer tank and other parameters on the impedance matching, and radiation pattern, aiming to enhance the sensitivity of the studied UHF PD sensor. A practical method for selecting the optimal frequency range for PD detection is proposed to improve the effectiveness of the UHF method and enhance the signal-to-noise ratio using frequency spectrum analysis. The results were validated by correlating the phase-resolved partial discharge (PRPD) patterns obtained through the IEC 60270 method with those from both a commercial sensor and the UHF PD sensor studied in this article. This validation confirms the effectiveness of the proposed approach in improving PD detection in power transformers.
AB - Advanced monitoring systems that combine PD detection with other methods, such as oil monitoring, increase reliability and provide operators with more accurate health assessments. This article studies the electromagnetic (EM) waves emitted from partial discharges in the ultra-high frequency (UHF) range using a special UHF sensor for integration purposes. Given the complex structure of power transformers, diagnosing partial discharges using UHF methods presents several challenges. This study addresses the impact of the transformer tank and other parameters on the impedance matching, and radiation pattern, aiming to enhance the sensitivity of the studied UHF PD sensor. A practical method for selecting the optimal frequency range for PD detection is proposed to improve the effectiveness of the UHF method and enhance the signal-to-noise ratio using frequency spectrum analysis. The results were validated by correlating the phase-resolved partial discharge (PRPD) patterns obtained through the IEC 60270 method with those from both a commercial sensor and the UHF PD sensor studied in this article. This validation confirms the effectiveness of the proposed approach in improving PD detection in power transformers.
KW - Partial discharge detection
KW - Power transformer diagnostics
KW - Signal-to-noise ratio enhancement
KW - UHF PD measurement
KW - UHF PD PRPD pattern
UR - http://www.scopus.com/inward/record.url?scp=85214404331&partnerID=8YFLogxK
U2 - 10.23919/CMD62064.2024.10766301
DO - 10.23919/CMD62064.2024.10766301
M3 - Conference contribution
AN - SCOPUS:85214404331
SN - 979-8-3503-5387-7
T3 - International Conference on Condition Monitoring and Diagnosis
SP - 13
EP - 16
BT - 2024 10th International Conference on Condition Monitoring and Diagnosis, CMD 2024
PB - Institute of Electrical and Electronics Engineers Inc.
T2 - 10th International Conference on Condition Monitoring and Diagnosis, CMD 2024
Y2 - 20 October 2024 through 24 October 2024
ER -