Abstract
| Original language | English |
|---|---|
| Title of host publication | 53rd International Universities Power Engineering Conference |
| Place of Publication | Piscataway, N.J. |
| Publisher | IEEE |
| Number of pages | 4 |
| Publication status | Accepted/In press - 11 Jul 2018 |
| Event | 53rd International Universities Power Engineering Conference - Glasgow Caledonian University, Glasgow, United Kingdom Duration: 4 Sep 2018 → 7 Sep 2018 Conference number: 53rd http://www.upec2018.com/ |
Conference
| Conference | 53rd International Universities Power Engineering Conference |
|---|---|
| Abbreviated title | UPEC 2018 |
| Country | United Kingdom |
| City | Glasgow |
| Period | 4/09/18 → 7/09/18 |
| Internet address |
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Keywords
- electrical condition assessment
- electro-magnetic interference
- partial discharge
- expert system
- pattern recognition
Cite this
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Classification of multiple electromagnetic interference events in high voltage power plant. / Mitiche, Imene; Morison, Gordon; Nesbitt, Alan; Hughes-Narborough, Michael; Stewart, Brian G.; Boreham, Philip.
53rd International Universities Power Engineering Conference. Piscataway, N.J. : IEEE, 2018.Research output: Chapter in Book/Report/Conference proceeding › Conference contribution book
TY - GEN
T1 - Classification of multiple electromagnetic interference events in high voltage power plant
AU - Mitiche, Imene
AU - Morison, Gordon
AU - Nesbitt, Alan
AU - Hughes-Narborough, Michael
AU - Stewart, Brian G.
AU - Boreham, Philip
PY - 2018/7/11
Y1 - 2018/7/11
N2 - This paper addresses condition assessment of electrical assets contained in high voltage power plants. Our work introduces a novel analysis approach of multiple event signals related to faults, and which are measured using Electro-Magnetic Interference method. The proposed method transfers the expert’s knowledge on events presence in the signals to an intelligent system which could potentially be used for automatic EMI diagnosis. Cyclic spectrum analysis is used as feature extraction to efficiently extract the repetitive rate and the dynamic discharge level of the events, and multi-class support vector machine is adopted for their classification. This first and novel method achieved successful results which may have potential implications on developing a framework for automatic diagnosis tool of EMI events.
AB - This paper addresses condition assessment of electrical assets contained in high voltage power plants. Our work introduces a novel analysis approach of multiple event signals related to faults, and which are measured using Electro-Magnetic Interference method. The proposed method transfers the expert’s knowledge on events presence in the signals to an intelligent system which could potentially be used for automatic EMI diagnosis. Cyclic spectrum analysis is used as feature extraction to efficiently extract the repetitive rate and the dynamic discharge level of the events, and multi-class support vector machine is adopted for their classification. This first and novel method achieved successful results which may have potential implications on developing a framework for automatic diagnosis tool of EMI events.
KW - electrical condition assessment
KW - electro-magnetic interference
KW - partial discharge
KW - expert system
KW - pattern recognition
UR - http://www.upec2018.com/
M3 - Conference contribution book
BT - 53rd International Universities Power Engineering Conference
PB - IEEE
CY - Piscataway, N.J.
ER -