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The development of prognostic tools for MV cable circuits

The development of prognostic tools for MV cable circuits
The development of prognostic tools for MV cable circuits
Cable failures are disruptive, costly to repair and have a serious impact on customer confidence. Thus developing a reliable on-line prognostic tool is of a great interest. An experimental setup has been created to develop a new prognostic thermal model for MV underground cables. This paper introduces a thermal prognostic simulation model based on Support Vector Regression Algorithm which predicts the likely temperature along the cable thirty minutes into the future and is able to detect temperature anomalies which can indicate upcoming failures.
condition monitoring, support vector regression, diagnostic, insulation system
978-1-4799-2789-0
249-253
Christou, S.
aa6be8f1-94a8-469c-84b1-ac90fcbf4a46
Lewin, P.L.
78b4fc49-1cb3-4db9-ba90-3ae70c0f639e
Pilgrim, J.A.
4b4f7933-1cd8-474f-bf69-39cefc376ab7
Swingler, S.G.
4f13fbb2-7d2e-480a-8687-acea6a4ed735
Christou, S.
aa6be8f1-94a8-469c-84b1-ac90fcbf4a46
Lewin, P.L.
78b4fc49-1cb3-4db9-ba90-3ae70c0f639e
Pilgrim, J.A.
4b4f7933-1cd8-474f-bf69-39cefc376ab7
Swingler, S.G.
4f13fbb2-7d2e-480a-8687-acea6a4ed735

Christou, S., Lewin, P.L., Pilgrim, J.A. and Swingler, S.G. (2014) The development of prognostic tools for MV cable circuits. 2014 IEEE Electrical Insulation Conference (EIC), United States. 08 - 11 Jun 2014. pp. 249-253 . (doi:10.1109/EIC.2014.6869386).

Record type: Conference or Workshop Item (Paper)

Abstract

Cable failures are disruptive, costly to repair and have a serious impact on customer confidence. Thus developing a reliable on-line prognostic tool is of a great interest. An experimental setup has been created to develop a new prognostic thermal model for MV underground cables. This paper introduces a thermal prognostic simulation model based on Support Vector Regression Algorithm which predicts the likely temperature along the cable thirty minutes into the future and is able to detect temperature anomalies which can indicate upcoming failures.

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More information

Published date: 8 June 2014
Venue - Dates: 2014 IEEE Electrical Insulation Conference (EIC), United States, 2014-06-08 - 2014-06-11
Keywords: condition monitoring, support vector regression, diagnostic, insulation system
Organisations: EEE

Identifiers

Local EPrints ID: 366646
URI: http://eprints.soton.ac.uk/id/eprint/366646
ISBN: 978-1-4799-2789-0
PURE UUID: 873dc4f0-a60c-4083-9718-5f8ef13b91ef
ORCID for J.A. Pilgrim: ORCID iD orcid.org/0000-0002-2444-2116

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Date deposited: 04 Jul 2014 11:27
Last modified: 03 Dec 2019 01:46

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Contributors

Author: S. Christou
Author: P.L. Lewin
Author: J.A. Pilgrim ORCID iD
Author: S.G. Swingler

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