Abstract: A brain-computer aided analysis method for an aviation accident is provided. The method includes the steps of obtaining historical electroencephalogram (EEG) signals and historical psychological and physiological features of various pilots during flight to be recorded as first EEG signals and first features; training a feature recognition model by using the first EEG signals as an input and the first features as an output; inputting EEG signals of a pilot of an aviation accident aircraft into the feature recognition model, and outputting psychological and physiological features of the pilot of the aviation accident aircraft to be recorded as second features; determining whether the second features are abnormal or not according to the historical psychological and physiological features of the pilot of the aviation accident aircraft and the first features.

Abstract: A variable-diameter blade suitable for a trans-media aircraft. The blade is divided into a blade root section, telescopic sections, and a blade tip section in a direction from the root to the tip. The blade further includes a telescopic rod, the blade root section and the blade tip section are fixed to the telescopic rod, respectively, and the telescopic rod is fixed to the trans-media aircraft; a spring arranged in the telescopic rod, the spring is used to drive the telescopic rod to extend; a pulley installed on the trans-media aircraft, the pulley is closer to the blade root section; a pull rope, an end of the pull rope passes through an inside of the blade and is fixed to the blade tip section, and the other end of the pull rope is wound on the pulley; and a driving device for driving the pulley to rotate.

Abstract: A brain-computer aided analysis method for an aviation accident is provided. The method includes the steps of obtaining historical electroencephalogram (EEG) signals and historical psychological and physiological features of various pilots during flight to be recorded as first EEG signals and first features; training a feature recognition model by using the first EEG signals as an input and the first features as an output; inputting EEG signals of a pilot of an aviation accident aircraft into the feature recognition model, and outputting psychological and physiological features of the pilot of the aviation accident aircraft to be recorded as second features; determining whether the second features are abnormal or not according to the historical psychological and physiological features of the pilot of the aviation accident aircraft and the first features.