An online condition monitoring thermal prognostic indicator system for MV cable circuits

Author

Christou, S. ; Lewin, P.L. ; Pilgrim, J.A. ; Swingler, S.G.

Author_Institution

Sch. of Electron. & Comput. Sci., Univ. of Southampton, Southampton, UK

fYear

2015

fDate

7-10 June 2015

Firstpage

535

Lastpage

538

Abstract

Developing a reliable online condition monitoring prognostic indicator tool for MV cables is of great importance as it can predict and prevent upcoming failures of the distribution cable circuits. This paper introduces a thermal prognostic model for MV underground cable terminations based on a support vector regression algorithm. The model is shown to predict the likely temperature along the cable thirty minutes into the future and is able to rapidly identify temperature anomalies which may indicate upcoming failures.

Keywords

condition monitoring; electric connectors; failure analysis; regression analysis; support vector machines; underground cables; MV cables; MV underground cable terminations; distribution cable circuits failures; online condition monitoring prognostic indicator tool; support vector regression algorithm; temperature anomalies; thermal prognostic model; Atmospheric modeling; Cable TV; Cable insulation; Data acquisition; Monitoring; Temperature measurement; Temperature sensors; Condition Monitoring; Diagnostic; Insulation System; Prognostic; Support Vector Regression;

fLanguage

English

Publisher

ieee

Conference_Titel

Electrical Insulation Conference (EIC), 2015 IEEE

Conference_Location

Seattle, WA

Print_ISBN

978-1-4799-7352-1

Type

conf

DOI

10.1109/ICACACT.2014.7223563

Filename

7223563