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DC Field | Value | Language |
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dc.contributor.author | Saleh, S.A. | - |
dc.contributor.author | Valdes, M. E. | - |
dc.contributor.author | Mardegan, C. | - |
dc.contributor.author | Alsayid, Basim | - |
dc.date.accessioned | 2019-06-18T04:45:04Z | - |
dc.date.available | 2019-06-18T04:45:04Z | - |
dc.date.issued | 2019-05 | - |
dc.identifier.uri | https://scholar.ptuk.edu.ps/handle/123456789/686 | - |
dc.description.abstract | This paper reviews approaches used to detect and identify arcing currents, including arcing current faults. The reviewed approaches are categorized as the time-domain, frequency-domain, and time-frequency approaches. The time-domain approach extracts shoulders (zero values of the current around zero crossing points), spikes and jumps, abnormal magnitudes (lower or higher than normal), and high rate of change of the current. The frequency-domain approach extracts the high frequency components, harmonic components, sub-harmonic components, and cross-correlation indicator. The time-frequency approach extracts high frequency sub-bands that contain nonstationary frequency components, which may have non-stationary phases. The three approaches are implemented to test their accuracy, computational requirements, and sensitivity to system parameters. These tests are performed by off-line processing of currents that are collected for normal and dynamic conditions, conventional faults, and currents with high or low arcing components. Test results provide a performance comparison for the tested approaches. | en_US |
dc.language.iso | en | en_US |
dc.publisher | 2019 IEEE/IAS 55th Industrial and Commercial Power Systems Technical | en_US |
dc.title | State-of-the-Art Methods for Detecting and Identifying Arcing Current Faults | en_US |
dc.type | Article | en_US |
Appears in Collections: | Engineering and Technology Faculty |
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