The University of Southampton
University of Southampton Institutional Repository

Wavelet packet denoising for online partial discharge detection in cables and its application to experimental field results

Record type: Article

Partial discharge measurements taken online are severely corrupted by noise due to external disturbances. In this paper a powerful noise reduction technique, based on a wavelet packet denoising algorithm, is employed to isolate the signals from the noise. This methodology enables the denoising of partial discharges that are heavily corrupted by noise without assuming any a priori knowledge about the partial discharge features. A brief description of the wavelet packet theory as an extension of the multi-resolution analysis is given. Results of the application of this algorithm to simulated data of low signal-to-noise ratio are presented, demonstrating substantial improvement in signal recovery with minimum shape distortion. Finally, the capability of this technique is highlighted by applying it to experimental field data taken from three-phase 11 kV cables.

PDF mst6_9_001.pdf - Other
Restricted to Registered users only
Download (1MB)

Citation

Kyprianou, A, Lewin, P L, Efthymiou, V, Stavrou, A and Georghiou, G E (2006) Wavelet packet denoising for online partial discharge detection in cables and its application to experimental field results Measurement Science and Technology, 17, (9), pp. 2367-2379.

More information

Published date: September 2006
Organisations: Electronics & Computer Science, EEE

Identifiers

Local EPrints ID: 262866
URI: http://eprints.soton.ac.uk/id/eprint/262866
ISSN: 0957-0233
PURE UUID: 3b219feb-d540-41f0-8cce-8d3eb2992412

Catalogue record

Date deposited: 25 Jul 2006
Last modified: 18 Jul 2017 08:47

Export record

Contributors

Author: A Kyprianou
Author: P L Lewin
Author: V Efthymiou
Author: A Stavrou
Author: G E Georghiou

University divisions


Download statistics

Downloads from ePrints over the past year. Other digital versions may also be available to download e.g. from the publisher's website.

View more statistics

Atom RSS 1.0 RSS 2.0

Contact ePrints Soton: eprints@soton.ac.uk

ePrints Soton supports OAI 2.0 with a base URL of http://eprints.soton.ac.uk/cgi/oai2

This repository has been built using EPrints software, developed at the University of Southampton, but available to everyone to use.

We use cookies to ensure that we give you the best experience on our website. If you continue without changing your settings, we will assume that you are happy to receive cookies on the University of Southampton website.

×