Intelligent PHM based Auxiliary Decision Framework of Advanced Modular Nuclear

As one of the innovative researches in the nuclear field, Advanced Modular Nuclear Systems (AMNS) has been wild concerned and paid more attention to the maintenance and safety problems. The rapid development of the sensors and the Internet of Things (IoT) technology provides a new opportunity for safeguard and operation maintenance for the AMNS. This paper proposes an Intelligent Prognostic and Health Management (PHM) based Auxiliary Decision framework. The designed framework acquires the data and uses emerging deep learning techniques to monitor the AMNS operations and diagnose the type and predict the trend of different accidents. Finally, the designed auxiliary decision framework will help operators respond rapidly and work far from accident influence. The proposed full-scope AMNS simulator platform provides the verification support of the whole framework. The experimental results verify the diagnosis and prediction efficiency of the proposed framework. Furthermore, this framework will provide guidance for the future application of deep learning-based PHM technology development in AMNS and other traditional third-generation reactors.