Cognitive load is generated by pilots in the process of information cognition about aircraft control, and it is closely related to flight safety. Cognitive load is the physiological and psychological need that a pilot produces when completing a mission. Therefore, it is meaningful to study the dynamic identification of the cognitive load of the pilot under the complex human-aircraft-environment interaction. In this paper, the airfield traffic pattern flight simulation experiment was designed and used to obtain the ECG physiological and NASA-TLX psychological data. The wavelet transform preprocessing and mathematical statistics analysis were applied on them, respectively. Furthermore, the Pearson correlation analysis method is used to select the characteristic indicators of psycho-physiological data after preprocessing. Based on the psycho-physiological characteristic indicators, the pilot’s cognitive load identification model is constructed by combining RNN and LSTM. The results of this study are more accurate compared with the cognitive load identification models established by other methods such as RNN neural network and support vector machine. This research is able to provide a useful reference for preventing and reduction of human error caused by the cognitive load during flight missions. It will be potential to realize intelligent control of aircraft cockpit, improving the flight control behavior and maintaining flight safety.
Due to its high bonding energy and low self-diffusion coefficient, silicon nitride (Si3N4) ceramics cannot form a dense structure with prolonged high-temperature insulation or by raising the sintering temperature. To improve the density of the sintered Si3N4 ceramics, additives are added to promote the rearrangement–dissolution–precipitation process of the crystal grains. However, the liquid phase formation temperature of different sintering aid chemical compositions varies, making it challenging to isolate the mechanism and the effect of liquid phase formation temperatures on sintering. Hence, we developed three sintering aids, namely Y2O3-Al2O3 (YA), Y2Si2O7 (Y2S), and Y2Si2O7-Al6Si2O13 (Y2SM), with homologous elements and different liquid phase formation temperatures. These sintering aids can form a liquid phase with SiO2 on the surface of Si3N4 at varying temperatures. We analyzed the sintered Si3N4 ceramic’s density, volume shrinkage rate, and microstructure to verify the YA’s lower liquid phase formation temperature effect, providing more rearrangement time and increasing sintering density. Conversely, sintering aids with too low liquid phase formation temperatures are more prone to volatilize during high-temperature sintering stages, thereby reducing sintering density. This research found that different liquid phase formation temperatures do not affect the α→β phase transition temperature of Si3N4 ceramics. We also evaluated the Y2S sintering aid contents’ effect on Si3N4 ceramics sintering. The results revealed that aiding sintering with too little Y2S content is insufficient for liquid phase production, and hence does not improve sintering density. Conversely, excessive liquid phase can improve density and refine grain size but increases weight loss rate during sintering due to volatilization.
scite is a Brooklyn-based organization that helps researchers better discover and understand research articles through Smart Citations–citations that display the context of the citation and describe whether the article provides supporting or contrasting evidence. scite is used by students and researchers from around the world and is funded in part by the National Science Foundation and the National Institute on Drug Abuse of the National Institutes of Health.