Interpretation of Frequency Response Analysis for Fault Detection in Power Transformers
Frequency response analysis (FRA) is a method of monitoring a power transformer’s mechanical integrity. However, identifying the type of fault and its severity by comparing measured responses is still challenging and mostly relies on personnel expertise. This paper is taking one step forward to stan...
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| Format: | Article |
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MDPI AG
2021-03-01
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| Series: | Applied Sciences |
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| Online Access: | https://www.mdpi.com/2076-3417/11/7/2923 |
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| author | Salem Mgammal Al-Ameri Muhammad Saufi Kamarudin Mohd Fairouz Mohd Yousof Ali A. Salem A. Abu Siada Mohamed I. Mosaad |
| author_facet | Salem Mgammal Al-Ameri Muhammad Saufi Kamarudin Mohd Fairouz Mohd Yousof Ali A. Salem A. Abu Siada Mohamed I. Mosaad |
| author_sort | Salem Mgammal Al-Ameri |
| collection | DOAJ |
| description | Frequency response analysis (FRA) is a method of monitoring a power transformer’s mechanical integrity. However, identifying the type of fault and its severity by comparing measured responses is still challenging and mostly relies on personnel expertise. This paper is taking one step forward to standardize the FRA interpretation process by proposing guidelines based on various international standards and FRA case studies. In this study, the FRA signature is divided into three regions: low-, mid- and high-frequency regions. The deviation from the fingerprint signature for various faults is classified into small, large, and no variations, based on the calculation of the correlation coefficient. The proposed guidelines are developed based on the frequency regions, and the level of variation is represented using a simple arrow method to simplify the interpretation process. A case study is conducted on a three-phase 11/0.433 kV, 500 kVA distribution transformer with a short circuit winding fault to validate the proposed guidelines. |
| first_indexed | 2024-03-10T12:56:04Z |
| format | Article |
| id | doaj.art-5f4a095f665c42c182e1a679e4b9202b |
| institution | Directory Open Access Journal |
| issn | 2076-3417 |
| language | English |
| last_indexed | 2024-03-10T12:56:04Z |
| publishDate | 2021-03-01 |
| publisher | MDPI AG |
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| series | Applied Sciences |
| spelling | doaj.art-5f4a095f665c42c182e1a679e4b9202b2023-11-21T11:55:47ZengMDPI AGApplied Sciences2076-34172021-03-01117292310.3390/app11072923Interpretation of Frequency Response Analysis for Fault Detection in Power TransformersSalem Mgammal Al-Ameri0Muhammad Saufi Kamarudin1Mohd Fairouz Mohd Yousof2Ali A. Salem3A. Abu Siada4Mohamed I. Mosaad5Department of Power Electrical, Faculty of Electrical and Electronic Engineering, University Tun Hussein Onn Malaysia, Batu Pahat 86400, Johor, MalaysiaDepartment of Power Electrical, Faculty of Electrical and Electronic Engineering, University Tun Hussein Onn Malaysia, Batu Pahat 86400, Johor, MalaysiaDepartment of Power Electrical, Faculty of Electrical and Electronic Engineering, University Tun Hussein Onn Malaysia, Batu Pahat 86400, Johor, MalaysiaDepartment of Power Electrical, Faculty of Electrical and Electronic Engineering, University Tun Hussein Onn Malaysia, Batu Pahat 86400, Johor, MalaysiaElectrical and Computer Engineering Department, Curtin University, Bentley, WA 6152, AustraliaElectrical and Electronics Engineering Technology Department, Yanbu Industrial College (YIC), Alnahdah, Yanbu Al Sinaiyah, Yanbu 46452, Saudi ArabiaFrequency response analysis (FRA) is a method of monitoring a power transformer’s mechanical integrity. However, identifying the type of fault and its severity by comparing measured responses is still challenging and mostly relies on personnel expertise. This paper is taking one step forward to standardize the FRA interpretation process by proposing guidelines based on various international standards and FRA case studies. In this study, the FRA signature is divided into three regions: low-, mid- and high-frequency regions. The deviation from the fingerprint signature for various faults is classified into small, large, and no variations, based on the calculation of the correlation coefficient. The proposed guidelines are developed based on the frequency regions, and the level of variation is represented using a simple arrow method to simplify the interpretation process. A case study is conducted on a three-phase 11/0.433 kV, 500 kVA distribution transformer with a short circuit winding fault to validate the proposed guidelines.https://www.mdpi.com/2076-3417/11/7/2923transformer faultsfrequency response analysisinterpretationcorrelation coefficient |
| spellingShingle | Salem Mgammal Al-Ameri Muhammad Saufi Kamarudin Mohd Fairouz Mohd Yousof Ali A. Salem A. Abu Siada Mohamed I. Mosaad Interpretation of Frequency Response Analysis for Fault Detection in Power Transformers Applied Sciences transformer faults frequency response analysis interpretation correlation coefficient |
| title | Interpretation of Frequency Response Analysis for Fault Detection in Power Transformers |
| title_full | Interpretation of Frequency Response Analysis for Fault Detection in Power Transformers |
| title_fullStr | Interpretation of Frequency Response Analysis for Fault Detection in Power Transformers |
| title_full_unstemmed | Interpretation of Frequency Response Analysis for Fault Detection in Power Transformers |
| title_short | Interpretation of Frequency Response Analysis for Fault Detection in Power Transformers |
| title_sort | interpretation of frequency response analysis for fault detection in power transformers |
| topic | transformer faults frequency response analysis interpretation correlation coefficient |
| url | https://www.mdpi.com/2076-3417/11/7/2923 |
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