Classification of multiple electromagnetic interference events in high voltage power plant

Imene Mitiche; Gordon Morison; Alan Nesbitt; Michael Hughes-Narborough; Brian G. Stewart; Philip Boreham

Classification of multiple electromagnetic interference events in high voltage power plant

Imene Mitiche, Gordon Morison, Alan Nesbitt, Michael Hughes-Narborough, Brian G. Stewart, Philip Boreham

Electronic And Electrical Engineering

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution book

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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	United Kingdom
City	Glasgow
Period	4/09/18 → 7/09/18
Internet address	http://www.upec2018.com/

Keywords

electrical condition assessment
electro-magnetic interference
partial discharge
expert system
pattern recognition

Access to Document

Mitiche-etal-IUPEC-2018-Classification-of-multiple-electromagnetic-interference-eventsAccepted author manuscript, 1.58 MB

http://www.upec2018.com/

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Cite this

@inproceedings{33deb6fa430c440fb7f9e6b962b817ab,

title = "Classification of multiple electromagnetic interference events in high voltage power plant",

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{\textquoteright}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.",

keywords = "electrical condition assessment, electro-magnetic interference, partial discharge, expert system, pattern recognition",

author = "Imene Mitiche and Gordon Morison and Alan Nesbitt and Michael Hughes-Narborough and Stewart, {Brian G.} and Philip Boreham",

year = "2018",

month = jul,

day = "11",

language = "English",

booktitle = "53rd International Universities Power Engineering Conference",

publisher = "IEEE",

note = "53rd International Universities Power Engineering Conference, UPEC 2018, UPEC 2018 ; Conference date: 04-09-2018 Through 07-09-2018",

url = "http://www.upec2018.com/",

}

Mitiche, I, Morison, G, Nesbitt, A, Hughes-Narborough, M, Stewart, BG & Boreham, P 2018, Classification of multiple electromagnetic interference events in high voltage power plant. in 53rd International Universities Power Engineering Conference. IEEE, Piscataway, N.J., 53rd International Universities Power Engineering Conference, UPEC 2018, Glasgow, United Kingdom, 4/09/18.

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

N1 - Conference code: 53rd

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.

T2 - 53rd International Universities Power Engineering Conference, UPEC 2018

Y2 - 4 September 2018 through 7 September 2018

ER -