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Detection of super-high-frequency partial discharge by using neural networks

Shan, Q. and Bhatti, S. and Glover, I.A. and Atkinson, R. and Rutherford, R. and , EPSRC (Funder) (2009) Detection of super-high-frequency partial discharge by using neural networks. Insight: The Journal of the British Institute of Non-Destructive Testing, 51 (8). pp. 442-447. ISSN 1354-2575

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Abstract

A system has been developed for the detection of super-high-frequency (SHF) partial discharge (PD) at frequencies up to 6 GHz. The system consists of three antennas for capturing PDs and a fast digital oscilloscope for sampling data. One of the antennas is a disk-cone antenna with frequency range below 710 MHz. The other two half TEM horn antennas have been designed and constructed for the frequency range 716 MHz - 5 GHz. To extend the frequency range up to 6 GHz, a methodology has been developed by compensating amplitude-response to frequency-magnitude. The compensation is realised by using multilayer feed-forward neural networks to equalise on amplitude-response. A direct sampling method is used to log the captured PD data. This PD detection system has been implemented to measure PDs at a 400 kV electrical substation (Strathaven, Scottish Power Ltd).

Item type: Article
ID code: 16727
Keywords: partial discharge, TEM horn, neural network, super high frequency, Electrical engineering. Electronics Nuclear engineering, Materials Chemistry, Mechanics of Materials, Metals and Alloys, Mechanical Engineering
Subjects: Technology > Electrical engineering. Electronics Nuclear engineering
Department: Faculty of Engineering > Electronic and Electrical Engineering
Related URLs:
    Depositing user: Dr Ian A Glover
    Date Deposited: 19 Mar 2010 15:47
    Last modified: 28 Mar 2014 05:21
    URI: http://strathprints.strath.ac.uk/id/eprint/16727

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