基于集成经验模态分解的飞行任务识别方法

Bi-Ting Yu, B. Jia, Qi Wu, Yanyu Lu, Dan Huang, Shan Fu
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引用次数: 0

摘要

为了分析飞行任务的难度,本文提出了一种利用飞行员瞳孔直径分析飞行任务难度的新方法。该方法结合集合经验模态分解(EEMD)和高低频小波系数能量比来识别5组学生不同任务下的瞳孔数据。与小波能量熵提取方法相比,该方法在手动偏离和标准仪器偏离之间的差异更明显。结果表明,飞行员的瞳孔直径可以区分飞行任务的难度。
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Identification of flight task using ensemble empirical mode decomposition based analysis method
To analyse the difficulty of flight tasks, a novel method was presented in this paper using pupil diameter of pilots. The proposed method integrated ensemble empirical mode decomposition (EEMD) and ratio of high to low frequency wavelet coefficients energy to identify pupil data under different tasks from 5 crews. Compared to the extraction method using wavelet energy entropy, the proposed method got more obvious difference between manual departure and standard instrument departure. The results indicated that the difficulty of flight tasks could be distinguished by pupil diameter of pilots.
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