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 1354-2575Full text not available in this repository. (Request a copy from the Strathclyde author)
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).
|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|
|Depositing user:||Dr Ian A Glover|
|Date Deposited:||19 Mar 2010 15:47|
|Last modified:||06 Jan 2017 07:56|