Understanding the Influence of Power Transformer Faults on the Frequency Response Signature Using Simulation Analysis and Statistical Indicators
Frequency Response Analysis (FRA) is the most reliable technique currently used to evaluate the mechanical integrity of power transformers. While the measurement devices have been well developed over the past two decades, interpretation of the FRA signatures is still challenging regardless of the se...
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| Format: | Article |
| Language: | English |
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IEEE
2021-01-01
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| Series: | IEEE Access |
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| Online Access: | https://ieeexplore.ieee.org/document/9420766/ |
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| author | Salem Mgammal Awadh Nasser Al-Ameri Muhammad Saufi Kamarudin Mohd Fairouz Mohd Yousof Ali A. Salem Fahd A. Banakhr Mohamed I. Mosaad A. Abu-Siada |
| author_facet | Salem Mgammal Awadh Nasser Al-Ameri Muhammad Saufi Kamarudin Mohd Fairouz Mohd Yousof Ali A. Salem Fahd A. Banakhr Mohamed I. Mosaad A. Abu-Siada |
| author_sort | Salem Mgammal Awadh Nasser Al-Ameri |
| collection | DOAJ |
| description | Frequency Response Analysis (FRA) is the most reliable technique currently used to evaluate the mechanical integrity of power transformers. While the measurement devices have been well developed over the past two decades, interpretation of the FRA signatures is still challenging regardless of the several papers published in this regard. This paper adds an attempt to understand the power transformer FRA signatures through experimental and simulation analyses. In this context, experimental FRA measurements are conducted on a 33/11 kV, 30 MVA transformer under various faults, including winding deformation, the short circuit turns, loss of clamping, and bushing fault. At the same time, the high-frequency transformer model that comprises series capacitance, self-inductance, series resistance, and mutual inductance is simulated using MATLAB / Simulink to compare simulation and experimental results. The correlation between physical circuit parameters and various faults facilitates a better understanding of each fault’s effect on the FRA signature. To quantify the impact of such faults, correlation coefficient, the absolute sum of logarithmic error, standard deviation, and sum square error are calculated with respect to the healthy signature at three frequency regions. Results show that using statistical coefficients over three frequency ranges of the FRA signature facilitates better fault identification and quantification. |
| first_indexed | 2024-12-22T00:16:10Z |
| format | Article |
| id | doaj.art-06b9502ce1bb41679d7568289b32843f |
| institution | Directory Open Access Journal |
| issn | 2169-3536 |
| language | English |
| last_indexed | 2024-12-22T00:16:10Z |
| publishDate | 2021-01-01 |
| publisher | IEEE |
| record_format | Article |
| series | IEEE Access |
| spelling | doaj.art-06b9502ce1bb41679d7568289b32843f2022-12-21T18:45:17ZengIEEEIEEE Access2169-35362021-01-019709357094710.1109/ACCESS.2021.30769849420766Understanding the Influence of Power Transformer Faults on the Frequency Response Signature Using Simulation Analysis and Statistical IndicatorsSalem Mgammal Awadh Nasser Al-Ameri0https://orcid.org/0000-0002-6693-8179Muhammad Saufi Kamarudin1Mohd Fairouz Mohd Yousof2https://orcid.org/0000-0002-1794-3406Ali A. Salem3https://orcid.org/0000-0002-0995-2791Fahd A. Banakhr4Mohamed I. Mosaad5https://orcid.org/0000-0002-6531-5455A. Abu-Siada6https://orcid.org/0000-0002-2094-3036Department of Electrical Power Engineering, Faculty of Electrical and Electronic Engineering, Universiti Tun Hussein Onn Malaysia, Johor, MalaysiaDepartment of Electrical Power Engineering, Faculty of Electrical and Electronic Engineering, Universiti Tun Hussein Onn Malaysia, Johor, MalaysiaDepartment of Electrical Power Engineering, Faculty of Electrical and Electronic Engineering, Universiti Tun Hussein Onn Malaysia, Johor, MalaysiaDepartment of Electrical Power Engineering, Faculty of Electrical and Electronic Engineering, Universiti Tun Hussein Onn Malaysia, Johor, MalaysiaYanbu Industrial College (YIC), Yanbu, Saudi ArabiaYanbu Industrial College (YIC), Yanbu, Saudi ArabiaElectrical and Computer Engineering Discipline, Curtin University, Bentley, WA, AustraliaFrequency Response Analysis (FRA) is the most reliable technique currently used to evaluate the mechanical integrity of power transformers. While the measurement devices have been well developed over the past two decades, interpretation of the FRA signatures is still challenging regardless of the several papers published in this regard. This paper adds an attempt to understand the power transformer FRA signatures through experimental and simulation analyses. In this context, experimental FRA measurements are conducted on a 33/11 kV, 30 MVA transformer under various faults, including winding deformation, the short circuit turns, loss of clamping, and bushing fault. At the same time, the high-frequency transformer model that comprises series capacitance, self-inductance, series resistance, and mutual inductance is simulated using MATLAB / Simulink to compare simulation and experimental results. The correlation between physical circuit parameters and various faults facilitates a better understanding of each fault’s effect on the FRA signature. To quantify the impact of such faults, correlation coefficient, the absolute sum of logarithmic error, standard deviation, and sum square error are calculated with respect to the healthy signature at three frequency regions. Results show that using statistical coefficients over three frequency ranges of the FRA signature facilitates better fault identification and quantification.https://ieeexplore.ieee.org/document/9420766/Power transformerfrequency response analysisfault diagnosisstatistical indicators |
| spellingShingle | Salem Mgammal Awadh Nasser Al-Ameri Muhammad Saufi Kamarudin Mohd Fairouz Mohd Yousof Ali A. Salem Fahd A. Banakhr Mohamed I. Mosaad A. Abu-Siada Understanding the Influence of Power Transformer Faults on the Frequency Response Signature Using Simulation Analysis and Statistical Indicators IEEE Access Power transformer frequency response analysis fault diagnosis statistical indicators |
| title | Understanding the Influence of Power Transformer Faults on the Frequency Response Signature Using Simulation Analysis and Statistical Indicators |
| title_full | Understanding the Influence of Power Transformer Faults on the Frequency Response Signature Using Simulation Analysis and Statistical Indicators |
| title_fullStr | Understanding the Influence of Power Transformer Faults on the Frequency Response Signature Using Simulation Analysis and Statistical Indicators |
| title_full_unstemmed | Understanding the Influence of Power Transformer Faults on the Frequency Response Signature Using Simulation Analysis and Statistical Indicators |
| title_short | Understanding the Influence of Power Transformer Faults on the Frequency Response Signature Using Simulation Analysis and Statistical Indicators |
| title_sort | understanding the influence of power transformer faults on the frequency response signature using simulation analysis and statistical indicators |
| topic | Power transformer frequency response analysis fault diagnosis statistical indicators |
| url | https://ieeexplore.ieee.org/document/9420766/ |
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