Jia Ming, Yang Gongliu. Type synthesis for sensing mechanism of superconductor gravity gradient based on constraint pattern[J]. Journal of Beijing University of Aeronautics and Astronautics, 2012, 38(12): 1606-1610. (in Chinese)
Citation: ZHU Linhao, ZOU Zehua, YIN Yin, et al. Intelligent design method of landing gear retraction and extension trajectory for narrow space[J]. Journal of Beijing University of Aeronautics and Astronautics, 2021, 47(12): 2560-2570. doi: 10.13700/j.bh.1001-5965.2020.0440(in Chinese)

Intelligent design method of landing gear retraction and extension trajectory for narrow space

doi: 10.13700/j.bh.1001-5965.2020.0440
Funds:

National Natural Science Foundation of China 51805249

Natural Science Foundation of Jiangsu Province BK20180436

the Fundamental Research Funds for the Central Universities NF2018001

Priority Academic Program Development of Jiangsu Higher Education Institutions 

More Information
  • Corresponding author: YIN Yin, E-mail: yinyin@nuaa.edu.cn
  • Received Date: 20 Aug 2020
  • Accepted Date: 21 Dec 2020
  • Publish Date: 20 Dec 2021
  • The flattened aerodynamic shape is the preferred layout for hypersonic vehicles to obtain high lift drag ratio, but this shape seriously restricts the collection space of the landing gear, and the conventional mechanism is difficult to meet the requirements. Engineers can only use the three-dimensional motion of the complex mechanism to realize the narrow space retraction and retraction of the landing gear. However, the current mainstream iterative trial and error method of computer-aided design relies heavily on engineering experience in solving the design problems of spatial mechanisms, which is time-consuming and labor-consuming, and it is difficult to obtain the optimal results. To address this problem, an intelligent optimization algorithm based method for autonomous design of complex landing gear mechanisms is proposed in this paper. First, theoretical kinematics model of retraction mechanism is built after analysis. Then, the model of inter-structure distances between landing gears and fuselage is established for detecting collisions, and the optimal motion trajectory of landing gear mechanisms is designed autonomously by using the deep neural network based learning optimization algorithm. Finally, the proposed method is applied to a landing gear mechanism design of certain hypersonic aircraft with a narrow cabin. The results show that the optimal design scheme for retractable mechanism can be obtained quickly by the proposed method, which can be used to guide the design of landing gear retractable mechanism for hypersonic aircraft.

     

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