Leak Detection for Self-Contained Fluid-Filled Cables using Regression Analysis


Hao, L, Lewin, P L, Swingler, S G and Bradley, C (2010) Leak Detection for Self-Contained Fluid-Filled Cables using Regression Analysis. In, IEEE 2010 International Symposium on Electrical Insulation, San Diego, California, USA, 06 - 09 Jun 2010. IEEE, CD-ROM.

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Description/Abstract

This paper investigates the methodology of the machine learning technique, namely the Support Vector Machine to assess the condition of fluid-filled high voltage cables based on thermal, pressure and load current information. Field data from a healthy circuit containing pressure, temperature and load current information have been obtained. The data structure has been investigated and a feasible algorithm to restructure the data for further analysis is proposed. The post-processing technique using Support Vector Machine Regression to predict oil pressure in the system is demonstrated. Results obtained using the regression analysis in this paper are very promising. Based on this method, an expert system could give early warning with better sensitivity than the existing system for the cable circuit and implementation of this approach can be achieved without taking the circuit out of service.

Item Type: Conference or Workshop Item (Paper)
Additional Information: Event Dates: 6 - 9 June 2010
ISBNs: 9781424463008
ISSNs: 1089-084X
Divisions: Faculty of Physical Sciences and Engineering > Electronics and Computer Science
Faculty of Physical Sciences and Engineering > Electronics and Computer Science > EEE
ePrint ID: 271224
Date Deposited: 06 Jun 2010 19:50
Last Modified: 27 Mar 2014 20:16
Publisher: IEEE
Contact Email Address: pll@ecs.soton.ac.uk
Further Information:Google Scholar
ISI Citation Count:0
URI: http://eprints.soton.ac.uk/id/eprint/271224

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