Abstract
Turn-to-turn short circuit fault is quite common in power and distribution transformers. This fault can be occurred due to the inter-turn paper insulation deterioration, or due to removing coated material between the winding turns. This study is focused to realize whether it is possible to recognize turn-to-turn fault using frequency response and vibration signatures in very early stages; before the insulation medium is totally deteriorated and a catastrophic failure is occurred for transformer. To this end, Frequency Response Analysis (FRA) and vibration techniques are introduced briefly. A 2 kVA three-phase transformer is used as a test object and turn-to-turn fault in one single disk of this transformer is emulated practically. The severity of the fault is changed through the controlling of the leakage short circuit current in faulty loop and FRA as well as vibration signatures are recorded. The results are demonstrated for each and every short circuit current and discussed in detail.
Original language | English |
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Title of host publication | 2016 International Conference on Smart Green Technology in Electrical and Information Systems: Advancing Smart and Green Technology to Build Smart Society, ICSGTEIS 2016 - Proceedings |
Publisher | Institute of Electrical and Electronics Engineers Inc. |
Pages | 10-15 |
Number of pages | 6 |
ISBN (Electronic) | 9781509026906 |
DOIs | |
Publication status | Published - Mar 23 2017 |
Event | 2016 International Conference on Smart Green Technology in Electrical and Information Systems, ICSGTEIS 2016 - Bali, Indonesia Duration: Oct 6 2016 → Oct 8 2016 |
Conference
Conference | 2016 International Conference on Smart Green Technology in Electrical and Information Systems, ICSGTEIS 2016 |
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Country/Territory | Indonesia |
City | Bali |
Period | 10/6/16 → 10/8/16 |
Keywords
- frequency response analysis
- transformer interturn fault
- vibration analysis
ASJC Scopus subject areas
- Renewable Energy, Sustainability and the Environment
- Electrical and Electronic Engineering
- Artificial Intelligence
- Computer Networks and Communications
- Hardware and Architecture
- Energy Engineering and Power Technology