Unsupervised machine learning techniques for fault detection and diagnosis in nuclear power plants

Develop an FDD approach based on unsupervised learning methods for NPPs. A comparative study on the presented methods is conducted. PCTRAN simulation is used to test the efficiencies of the proposed approach. Nuclear power plants have proved their importance in the energy sector by generating clean and uninterrupted energy over decades. Moreover, nuclear power plants (NPPs) are large-scale and complex systems with potential radioactive release risks.