Architecture Design and Implementation of the Nuclear Reactor Big Data System (Ruilong System)

This paper introduces the data architecture design of the nuclear reactor big data system. By identifying business objects, a flexible and stable data business model has been constructed, forming a complete, standardized and accurate data system that logically integrates multi-source and heterogeneous data. In cases where label information is missing, a high-performance label annotation tool has been developed using semi-supervised learning methods and applied to unstructured data and time-series data. For different types of data missing, methods based on mechanisms, statistics, and machine learning are used to repair and filter anomalies in the data. Through critical domain analysis and architectural design, a software view characterized by clear layers, strong scalability and high flexibility has been established. This effectively avoids design iterations and ensures development quality. To further enhance the maturity of nuclear reactor big data technology, the next phase will focus on improving data governance, data value mining and intelligent operation and maintenance capabilities, ensuring the long-term safe and reliable operation of nuclear reactor facilities.