Title :
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
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;
Conference_Titel :
Electrical Insulation Conference (EIC), 2015 IEEE
Conference_Location :
Seattle, WA
Print_ISBN :
978-1-4799-7352-1
DOI :
10.1109/ICACACT.2014.7223563
