The University of Southampton
University of Southampton Institutional Repository

Phase Resolved Partial Discharge Identification using a Support Vector Machine

Hao, L and Lewin, P L (2008) Phase Resolved Partial Discharge Identification using a Support Vector Machine At 23rd IAR Workshop on Advanced Control and Diagnosis, United Kingdom. 27 - 28 Nov 2008. , pp. 386-391.

Record type: Conference or Workshop Item (Paper)


Partial discharge (PD) has a significant effect on the insulation performance of power apparatus in both transmission and distribution networks of power systems. Insulation performance and properties can be influenced by different types of PD activity. Therefore, PD source identification and diagnosis is of interest to both power equipment Manufacturers and utilities. With developments in measurement techniques, sensors and signal processing techniques, interpretation of the measured PD data and PD source identification are gaining more interest. Over the last two decades, research into computer-aided automatic PD source discrimination has attracted great attention. A number of papers have been published based on the use of artificial intelligence algorithms such as artificial neural networks, genetic algorithms and fuzzy logic. This paper investigates the application of a machine learning technique, namely the support vector machine (SVM) on PD source identification using phase resolved discharge distribution information (' – average q). PD data obtained from a conventional PD detector and a non-conventional radio frequency current transducer were used to assess the performance of the use of a phase resolved parameter for identification.

PDF IAR-ACD2008southampton.pdf - Author's Original
Restricted to Registered users only
Download (971kB)

More information

Published date: 27 November 2008
Additional Information: Event Dates: 27-28 November 2008
Venue - Dates: 23rd IAR Workshop on Advanced Control and Diagnosis, United Kingdom, 2008-11-27 - 2008-11-28
Organisations: Electronics & Computer Science, EEE


Local EPrints ID: 266971
PURE UUID: ce381fa7-2dc6-4368-beba-66f5003ef77b

Catalogue record

Date deposited: 08 Dec 2008 18:46
Last modified: 18 Jul 2017 07:09

Export record


Author: L Hao
Author: P L Lewin

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 supports OAI 2.0 with a base URL of

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.