Digital Twin and Machine Learning Framework for Predictive Maintenance of Nuclear Power Systems
Nuclear power systems contain safety-critical components whose degradation can affect availability, reliability, and maintenance planning. Conventional maintenance strategies are largely based on scheduled inspection, threshold monitoring, and condition-based assessment, which may not fully exploit the large volume of continuously generated plant data.
Digital Twin, Nuclear Power System, Machine Learning, Predictive Maintenance, Fault Diagnosis