Failure prediction of power cables using failure history and operational conditions

Research output: Chapter in Book/Report/Conference proceedingChapter (peer-reviewed)

Published

DOI

View graph of relations

Original languageEnglish
Title of host publicationProperties and Applications of Dielectric Materials (ICPADM), 2015 IEEE 11th International Conference on the
Place of PublicationSydney, NSW
PublisherIEEE
Pages380-383
Number of pages4
ISBN (Electronic)9781479989034
DOIs
StatePublished - 15 Oct 2015

Conference

Conference2015 IEEE 11th International Conference on the Properties and Applications of Dielectric Materials (ICPADM)
CountryAustralia
CitySydney
Dates19/07/1522/07/15

Abstract

This paper classifies the causes of cable failures according to two types: unpredictable random causes; and predictable ageing effects. A piecewise power-law non-homogeneous Poisson process and a stochastic electro-thermal model are proposed to predict total annual failures and failures due specifically to ageing, respectively. An amalgamation of the two models is then used to estimate the number of failures attributable to random causes or ageing. The proposed method is successfully applied to real data of vintage unjacketed XLPE cables. The results show that these cables have an expected lifespan of 39 years based on ageing effects alone; however, failure of these cables is dominated by random failure modes such as manufacturing defects, sudden shock, or water and electrical tree, which cause many of these cables to fail earlier in their life.

Keywords

  • XLPE insulation, ageing, failure analysis, power cable insulation, prediction theory, stochastic processes, failure history, operational conditions, piecewise power-law nonhomogeneous Poisson process, power cable failure prediction, predictable ageing effects, stochastic electrothermal model, total annual failure prediction, unpredictable random causes, vintage unjacketed XLPE cable, Aging, Cable insulation, Communication cables, Data models, Degradation, Power cables, Stress, electro-thermal, poisson process, random failure