关键词: 文本挖掘(TM), 人因分析与分类系统(HFACS), 功能共振分析法(FRAM), 管制运行, 不安全事件, 致因分析

Abstract:

In order to improve the systematicity and objectivity of safety risk identification in civil aviation ATC operations and to explore the causes and interaction relationships of ATC unsafe incidents, a causal analysis method for ATC unsafe incidents was proposed, integrating TM, HFACS, and FRAM. Firstly, TM technology was employed to perform text processing on unsafe incident reports, and high-frequency keywords related to ATC operation risks were extracted using the Term Frequency-Inverse Document Frequency (TF-IDF) method. Secondly, semantic attribution was conducted on these keywords, and an improved multi-level HFACS framework for ATC operations was constructed based on the characteristics of ATC work, and the corresponding risk factors were determined. Then, the interdependent relationships between various functional modules in the ATC operation system were analyzed by introducing FRAM to reveal the potential impact of interactions within the complex ATC system on incident occurrence. Finally, two cases of ATC unsafe incidents were investigated to analyze their risk causes. The results show that the proposed method effectively mines the interrelationships between multi-source causes and identifies multi-level risk causal factors, which verifies the effectiveness and scientific rigor of the method in multi-source data processing and complex causal structure mining.

Key words: text mining (TM), human factors analysis and classification system (HFACS), functional resonance analysis method (FRAM), air traffic control(ATC) operation, unsafe event, causation analysis