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Exploring Data Collection and Fusion of Medium Voltage Cable Failures - A Danish Case Study (Authors Version)

Authors: Konrad Sundsgaard; Jens Zoëga Hansen; Guangya Yang; Massimo Cafaro; Peter Kjær Hansen;

Exploring Data Collection and Fusion of Medium Voltage Cable Failures - A Danish Case Study (Authors Version)

Abstract

The modernisation of medium voltage cable systems must be prioritised effectively. Fortunately, there exist methods which can rank cables by health and thus schedule investments properly. Thereby, many approaches benefit greatly from historical failure data. However, if available, failure records rarely include all required features, such as cable age or location. Consequently, strategies for collecting these characteristics are needed for modelling success. This study uses the Danish database for distribution grid failures as a case study to elaborate on effective approaches to obtain more complete raw failure records. After highlighting missing information in the available data, several data collection and fusion strategies are applied, including joins with further asset registers from distribution system operators.

Keywords

Failure data, medium voltage cables, reliability, asset management, machine learning, data fusion, Failure data, medium voltage cables, reliability, asset management, machine learning, data fusion

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selected citations
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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).
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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!
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