Abstract
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.
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, UPEC 2018 - 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, UPEC 2018 |
---|---|
Abbreviated title | UPEC 2018 |
Country/Territory | United Kingdom |
City | Glasgow |
Period | 4/09/18 → 7/09/18 |
Internet address |
Keywords
- electrical condition assessment
- electro-magnetic interference
- partial discharge
- expert system
- pattern recognition