Multi-Kernel Support Vector Machine based Predictive Maintenance of Circulating Water Pumps in Nuclear Power Plants

Multi-Kernel Support Vector Machine (MK-SVM) is a machine learning classification algorithm that can assist in the development of predictive maintenance strategies for nuclear power plant systems. Predictive maintenance can alleviate maintenance costs and enhance reliability of plant systems. In thi...

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Bibliographic Details
Main Authors Scott, Matthew Stephen, Agarwal, Vivek, Araseethota Manjunatha, Koushik
Format Conference Proceeding
LanguageEnglish
Published United States 11.08.2022
Subjects
INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND TECHNOLOGY
Machine Learning
Predictive Maintenance
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Summary:Multi-Kernel Support Vector Machine (MK-SVM) is a machine learning classification algorithm that can assist in the development of predictive maintenance strategies for nuclear power plant systems. Predictive maintenance can alleviate maintenance costs and enhance reliability of plant systems. In this work, MK-SVM is utilized for determining the health of the circulating water system (CWS) in a nuclear power plant.
Bibliography:DE-AC07-05ID14517
USDOE Office of Nuclear Energy (NE)
INL/EXP-22-68377-Rev000