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image/svg+xml Jakob Voss, based on art designer at PLoS, modified by Wikipedia users Nina and Beao Closed Access logo, derived from PLoS Open Access logo. This version with transparent background. http://commons.wikimedia.org/wiki/File:Closed_Access_logo_transparent.svg Jakob Voss, based on art designer at PLoS, modified by Wikipedia users Nina and Beao IEEE Transactions on...arrow_drop_down
image/svg+xml Jakob Voss, based on art designer at PLoS, modified by Wikipedia users Nina and Beao Closed Access logo, derived from PLoS Open Access logo. This version with transparent background. http://commons.wikimedia.org/wiki/File:Closed_Access_logo_transparent.svg Jakob Voss, based on art designer at PLoS, modified by Wikipedia users Nina and Beao
IEEE Transactions on Power Delivery
Article . 2022 . Peer-reviewed
License: IEEE Copyright
Data sources: Crossref
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Remaining Useful Life Prediction of Aerial Bundled Cables in Coastal Areas Using Thermal and Corrosion Degradation Models

Authors: Waleed Bin Yousuf; Tariq Mairaj Rasool Khan; Syed Talha Tariq; Moez ul-Hassan; Aqueel Shah;

Remaining Useful Life Prediction of Aerial Bundled Cables in Coastal Areas Using Thermal and Corrosion Degradation Models

Abstract

Insulated aerial bundled cables (ABCs) are preferred over conventional bare conductor cables in electrical distribution system as ABCs are more safe, less prone to electricity pilferage and offers higher reliability. However, the degradation phenomenon of ABCs is sudden as compared to conventional cables especially in coastal areas. Sudden failures of ABCs in coastal areas make the maintenance planning challenging. Hence, accurate reliability estimation is required which can enable timely maintenance planning and in turn reducing the chances of failures. A novel reliability model is reported in this work which is derived from historical failure data of particular type of ABCs coupled with the degradation models. The models are based upon the actual environmental conditions experienced by the cables under study. The actual loading data as well as environmental data of two sites of varying distance from Seashore are used to develop the respective reliability models. The reliability prediction from proposed reliability model is then validated using time to failure computation through comparison of historical infrared thermography based Non-destructive testing (NDT) data, acquired at the sites under study, with reference to NDT measurements acquired from the ruptured/failed cable. The validation indicates the efficacy of the proposed reliability model.

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    citations
    This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
    4
    popularity
    This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
    Top 10%
    influence
    This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
    Average
    impulse
    This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
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Found an issue? Give us feedback
citations
This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Citations provided by BIP!
popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
BIP!Impulse provided by BIP!
4
Top 10%
Average
Average