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
8 June 2014
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), Philadelphia, United States.
08 - 11 Jun 2014.
.
(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), Philadelphia, 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
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Date deposited: 04 Jul 2014 11:27
Last modified: 15 Mar 2024 03:25
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Contributors
Author:
S. Christou
Author:
P.L. Lewin
Author:
J.A. Pilgrim
Author:
S.G. Swingler
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