Image processing-based on-line technique to detect power transformer winding faults
Frequency Response Analysis (FRA) has been growing in popularity in recent times as a tool to detect mechanical deformation within power transformers. To conduct the test, the transformer has to be taken out of service which may cause interruption to the electricity grid. Moreover, because FRA relie...
| Main Authors: | , |
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| Other Authors: | |
| Format: | Conference Paper |
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IEEE Industrial Electronics Society
2013
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| Online Access: | http://hdl.handle.net/20.500.11937/6635 |
| _version_ | 1848745134117617664 |
|---|---|
| author | Abu-Siada, Ahmed Islam, Syed |
| author2 | IEEE Industrial Electronics Society |
| author_facet | IEEE Industrial Electronics Society Abu-Siada, Ahmed Islam, Syed |
| author_sort | Abu-Siada, Ahmed |
| building | Curtin Institutional Repository |
| collection | Online Access |
| description | Frequency Response Analysis (FRA) has been growing in popularity in recent times as a tool to detect mechanical deformation within power transformers. To conduct the test, the transformer has to be taken out of service which may cause interruption to the electricity grid. Moreover, because FRA relies on graphical analysis, it calls for an expert person to analyse the results as so far, there is no standard code for FRA interpretation worldwide. In this paper an online technique is introduced to detect the internal faults within a power transformer by constructing the voltage-current (V-I) locus diagram to provide a current state of the transformer health condition. The technique does not call for any special equipment as it uses the existing metering devices attached to any power transformer to monitor the input voltage, output voltage and the input current at the power frequency and hence online monitoring can be realised. Various types of faults have been simulated to assess its impact on the proposed locus. A Matlab code based on digital image processing is developed to calculate any deviation of the V-I locus with respect to the reference one and to identify the type of fault. |
| first_indexed | 2025-11-14T06:12:31Z |
| format | Conference Paper |
| id | curtin-20.500.11937-6635 |
| institution | Curtin University Malaysia |
| institution_category | Local University |
| last_indexed | 2025-11-14T06:12:31Z |
| publishDate | 2013 |
| publisher | IEEE Industrial Electronics Society |
| recordtype | eprints |
| repository_type | Digital Repository |
| spelling | curtin-20.500.11937-66352017-01-30T10:54:16Z Image processing-based on-line technique to detect power transformer winding faults Abu-Siada, Ahmed Islam, Syed IEEE Industrial Electronics Society Frequency Response Analysis (FRA) has been growing in popularity in recent times as a tool to detect mechanical deformation within power transformers. To conduct the test, the transformer has to be taken out of service which may cause interruption to the electricity grid. Moreover, because FRA relies on graphical analysis, it calls for an expert person to analyse the results as so far, there is no standard code for FRA interpretation worldwide. In this paper an online technique is introduced to detect the internal faults within a power transformer by constructing the voltage-current (V-I) locus diagram to provide a current state of the transformer health condition. The technique does not call for any special equipment as it uses the existing metering devices attached to any power transformer to monitor the input voltage, output voltage and the input current at the power frequency and hence online monitoring can be realised. Various types of faults have been simulated to assess its impact on the proposed locus. A Matlab code based on digital image processing is developed to calculate any deviation of the V-I locus with respect to the reference one and to identify the type of fault. 2013 Conference Paper http://hdl.handle.net/20.500.11937/6635 IEEE Industrial Electronics Society fulltext |
| spellingShingle | Abu-Siada, Ahmed Islam, Syed Image processing-based on-line technique to detect power transformer winding faults |
| title | Image processing-based on-line technique to detect power transformer winding faults |
| title_full | Image processing-based on-line technique to detect power transformer winding faults |
| title_fullStr | Image processing-based on-line technique to detect power transformer winding faults |
| title_full_unstemmed | Image processing-based on-line technique to detect power transformer winding faults |
| title_short | Image processing-based on-line technique to detect power transformer winding faults |
| title_sort | image processing-based on-line technique to detect power transformer winding faults |
| url | http://hdl.handle.net/20.500.11937/6635 |