防人因失误的智能化分析与辅助工具研究进展OA

To address safety challenges arising from the digital transformation of nuclear power plant control rooms,a structured analytical framework for operator error prevention is developed.Rather than enumerating individual technolo-gies,the paper traces the technical evolution of intelligent human reliability analysis(HRA)and clarifies three major development stages.The first stage focuses on knowledge-graph-based semantic modeling of human-machine interfaces to maintain cognitive consistency between procedures and interface operations.The second stage introduces machine learning and cognitive modeling techniques to estimate operator states in real time,thereby improving transparency of performance dynamics.The third stage explores the use of large language models to support proactive human-machine co-intervention for risk interruption.For each stage,the underlying technical mechanisms are examined and compared with traditional HRA approaches.The results indicate that intelligent methods offer improved data utilization,finer-grained assessment,and enhanced responsiveness in dynamic operational contexts.At the same time,issues related to model reliability and interpretability remain critical and require further attention.By integrating these developments,the study outlines a technical system for intelligent human factor analysis in digital main control rooms and provides a foun-dation for future engineering implementation and methodological refinement of intelligent HRA.