Automated feature validation of trip coil analysis in condition monitoring of circuit breakers
Hosseini, Michael and Helm, Joseph and Stephen, Bruce and McArthur, Stephen D. J. (2018) Automated feature validation of trip coil analysis in condition monitoring of circuit breakers. PHM Society European Conference, 4 (1). (https://phmpapers.org/index.php/phme/article/view/...)
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Abstract
Datasets of historical performance metrics can offer valuable insight into an asset fleet’s health. This is especially so in the context to establishing normal behavior and thresholds of acceptable performance for diagnostic purposes. However, plant performance can often be obscured by data quality issues which introduce artefacts that do not pertain to asset health. This paper utilises a supervised ensemble machine-learning approach to automate the process of filtering maintenance data based on their predicted validity. The results are then presented both in terms of classification performance, and the impact on the distributions directly. This helps to ensure engineers are basing their diagnostic decisions on valid data. The accuracy of the filtration process, and its effect on the final thresholds will be discussed. To illustrate, this paper uses data of varying quality on circuit breaker trip tests obtained from operational medium-voltage circuit-breakers spanning several decades with the aim of providing decision support for switchgear diagnostics.
ORCID iDs
Hosseini, Michael ORCID: https://orcid.org/0000-0002-4023-8414, Helm, Joseph, Stephen, Bruce ORCID: https://orcid.org/0000-0001-7502-8129 and McArthur, Stephen D. J. ORCID: https://orcid.org/0000-0003-1312-8874;-
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Item type: Article ID code: 64783 Dates: DateEvent1 July 2018Published31 May 2018AcceptedSubjects: Technology > Electrical engineering. Electronics Nuclear engineering Department: Faculty of Engineering > Electronic and Electrical Engineering Depositing user: Pure Administrator Date deposited: 12 Jul 2018 14:45 Last modified: 11 Nov 2024 12:03 Related URLs: URI: https://strathprints.strath.ac.uk/id/eprint/64783