计算机工程与应用 ›› 2024, Vol. 60 ›› Issue (20): 84-95.DOI: 10.3778/j.issn.1002-8331.2403-0135

• 热点与综述 • 上一篇    下一篇

航空人员疲劳检测方法研究

张荣,梁馨月   

  1. 中国民航大学 安全科学与工程学院,天津 300300
  • 出版日期:2024-10-15 发布日期:2024-10-15

Research on Fatigue Detection Methods for Aviation Personnel

ZHANG Rong, LIANG Xinyue   

  1. Faculty of Safety Science and Engineering, Civil Aviation University of China, Tianjin 300300, China
  • Online:2024-10-15 Published:2024-10-15

摘要: 航空人员疲劳问题一直受到民航业的广泛关注,为减少由疲劳问题带来的民航运行风险,综合分析了民航领域下的航空人员疲劳研究现状,梳理当前疲劳研究成果,为航空领域的疲劳研究提供新的思路。明确了航空人员疲劳概念及其影响因素;从生理指标、主观测评两个检测方法维度对飞行员、空中交通管制员和机务维修人员的疲劳研究进行对比分析,并结合计算机检测方法,对飞行员和空中交通管制员的疲劳检测模型进行梳理总结;根据研究梳理提出当前疲劳检测的不足之处及发展方向。研究结果表明:客观检测手段逐渐趋于成熟,生理指标被广泛应用于疲劳检测中;疲劳检测模型的指标选取有待于进一步研究,模型识别准确性及疲劳分类精度有待提高,尤其是机务人员疲劳检测模型尚不成熟;未来驾驶舱高度自动化环境下的自动驾驶及人机功能分配问题带来的被动疲劳是研究重点。

关键词: 航空人员, 疲劳检测, 生理指标, 主观测评, 判别模型

Abstract: The fatigue problem for aviation personnel has attracted attention in civil aviation, in order to reduce the risk of civil aviation operation caused by fatigue problems, the development status of aviation personnel fatigue research under the field of civil aviation is analyzed, and the current fatigue research results are sorted out and future development of fatigue detection in civil aviation is put forward. Firstly, the concept of fatigue of aviation personnel and its influencing factors are clarified. Then, the fatigue studies of pilots, air traffic controllers and aircraft maintenance personnel are compared and analyzed from the dimensions of physiological indicators and subjective measurement methods, and the fatigue detection models of pilots and air traffic controllers  are sorted out and summarized by combining the computerized detection methods. Finally, the shortcomings and development direction of the current fatigue detection are put forward according to the research. The results show that the objective detection methods are gradually becoming mature, and physiological indicators are widely used in fatigue detection. The selection of indicators for fatigue detection models needs to be further studied, and the accuracy of model identification and fatigue classification needs to be improved, especially the fatigue detection model for maintenance personnel needs to be developed. In the future, passive fatigue caused by automated driving and human-machine function allocation problems in highly automated cockpit environment is the focus of research.

Key words: aviation personnel, fatigue detection, physiological indicator, subjective evaluation, discriminant model