Abstract
In order to determine the factors that affect the static comfort of ejection seats, an intelligent monitoring method for static safety of ejection seats based on human factors engineering is proposed. Human factors engineering is used to analyze human motion, and different percentiles of human body size are used to simulate the leg motion range, so as to determine the travel and adjustment amount of the pedal. Combined with the size of the human body, the position of the seat reference point and the comfort Angle of each joint of the human leg, the comfort range of the pedal shaft is solved, and the pedal is optimized. The finite element model of the ejection seat is constructed by human factors engineering, and the linear elastic constitutive relationship is used as the material constitutive relationship of the ejection seat. The material density, Young's modulus, Poisson's ratio, shear modulus, bulk modulus and other parameters are defined to analyze the impact load of the ejection seat when it is ejected. The results indicate that the finite element model based on ergonomics is suitable for static comfort monitoring of ejection seats. The increase in seat cushion thickness has a certain trend of reducing the maximum and average pressure in certain areas of the seat cushion, and has almost no effect on the contact area. Increasing the protrusion of the waist can increase the maximum pressure on the waist, but it will reduce the contact area at the shoulder position. In the development of comfort, attention should be paid to the matching of the waist and shoulders to ensure the overall comfort of the backrest.
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A school-level project of Beijing Polytechnic, Project Name: Research on layout design and static comfort simulation of ejection seat based on human factors engineering (KM202210858003).
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© 2024 ICST Institute for Computer Sciences, Social Informatics and Telecommunications Engineering
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Shi, J., Ma, C. (2024). Intelligent Monitoring Method for Static Comfort of Ejection Seat Based on Human Factors Engineering. In: Yun, L., Han, J., Han, Y. (eds) Advanced Hybrid Information Processing. ADHIP 2023. Lecture Notes of the Institute for Computer Sciences, Social Informatics and Telecommunications Engineering, vol 550. Springer, Cham. https://doi.org/10.1007/978-3-031-50552-2_1
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DOI: https://doi.org/10.1007/978-3-031-50552-2_1
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