| dc.contributor.author | Ashoor, M. | en_US |
| dc.date.accessioned | 1399-07-08T21:54:10Z | fa_IR |
| dc.date.accessioned | 2020-09-29T21:54:10Z | |
| dc.date.available | 1399-07-08T21:54:10Z | fa_IR |
| dc.date.available | 2020-09-29T21:54:10Z | |
| dc.date.issued | 2008-04-01 | en_US |
| dc.date.issued | 1387-01-13 | fa_IR |
| dc.date.submitted | 2009-05-30 | en_US |
| dc.date.submitted | 1388-03-09 | fa_IR |
| dc.identifier.citation | Ashoor, M.. (2008). New Wavelet-Based Approach for Internal Fault Current Identi cation in Power Transformers. Scientia Iranica, 15(2) | en_US |
| dc.identifier.issn | 1026-3098 | |
| dc.identifier.issn | 2345-3605 | |
| dc.identifier.uri | http://scientiairanica.sharif.edu/article_2964.html | |
| dc.identifier.uri | https://iranjournals.nlai.ir/handle/123456789/120581 | |
| dc.description.abstract | This paper demonstrates a novel approach for the di erential protection of power transformers.
This method uses the Wavelet Transform (WT) and the Adaptive Network-based Fuzzy Inference
System (ANFIS) to detect a fault current from an inrush current. The proposed method has
been designed, based on the di erences between the amplitudes of wavelet transform coe cients
in a special band of frequency that is caused by faults and inrush currents. The performance of
this algorithm has been simulated and tested under di erent conditions of the switching on of
power transformers, using the PSCAD/EMTDC environment software. | en_US |
| dc.format.extent | 2041 | |
| dc.format.mimetype | application/pdf | |
| dc.language | English | |
| dc.language.iso | en_US | |
| dc.publisher | Sharif University of Technology | en_US |
| dc.relation.ispartof | Scientia Iranica | en_US |
| dc.title | New Wavelet-Based Approach for Internal Fault Current Identi cation in Power Transformers | en_US |
| dc.type | Text | en_US |
| dc.contributor.department | Department of Electrical Engineering,University of Tehran | en_US |
| dc.citation.volume | 15 | |
| dc.citation.issue | 2 | |
