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运载火箭电缆自适应布局技术研究

Research on Adaptive Layout Technology of Launch Vehicle Cable
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摘要 电气系统是运载火箭的重要组成部分,传统火箭布局是将仪器设备布局和电缆走线两个阶段串联运行的设计模式,布局方式大多都依靠经验,割裂了仪器布局与电缆走线之间的耦合关系,不仅效率较低,而且可能造成电缆总重量难以有效优化,从而降低运载火箭的运载能力。本文提出一种基于智能算法的仪器电缆自适应快速布局技术,将设备布局和电缆走线协同优化设计,实现壳段上仪器电缆的快速、智能设计,从而大幅提升设计效率,该技术已成功应用到我国最大的固体运载火箭“力箭一号”设计中,火箭在2022年7月27日完成圆满首飞。 The electrical system is an important part of the launch vehicle.The traditional layout is designed that the instrument and equipment layout and cable routing are operated in series.The layout mode mostly depends on experience,and do not the coupled relationship between the instrument layout and cable routing,which is not only inefficient,but also may cause the total weight of the cable to be difficult to effectively optimize,thus reducing the launch vehicleʼs carrying capacity.In this paper,an adaptive fast layout technology of instrument cable based on intelligent algorithm is proposed,which optimizes the layout of equipment and cable routing to realize the rapid and intelligent design of instrument cable on shell section,thus greatly improving the design efficiency and applying it to launch vehicle.This technology has been successfully applied in Chinaʼs largest solid launch vehicle“PR-1”,and the rocket completed its successful first flight on July 27,2022.
作者 杨浩亮 龙舟 王瑀宁 吕超 Yang Haoliang;Long Zhou;Wang Yuning;Lv Chao(Beijing CAS Space Corporation,Beijing 100176;China Intentional Engineering Consulting Corporation,Beijing 100048)
出处 《航天制造技术》 2023年第1期11-15,共5页 Aerospace Manufacturing Technology
基金 临近空间中高层科学探测与实验系统集成与验证(Y820082XD2)。
关键词 运载火箭仪器电缆 自适应 智能布局 最大的固体运载火箭“力箭一号” launch vehicle instrument cable adaptive intelligent layout largest solid launch vehicle“PR-1”
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  • 1刁常堃,刘刚,侯向阳,王威.基于Pro/E软件的电缆三维设计及制造方法[J].航天制造技术,2013(2):46-48. 被引量:15
  • 2任彦,张思东,张宏科.无线传感器网络中覆盖控制理论与算法[J].软件学报,2006,17(3):422-433. 被引量:156
  • 3陆欣星,邹北骥,彭小宁,刘丽丽.一种优化的二次接线自动生成方法研究[J].工程图学学报,2006,27(4):31-37. 被引量:2
  • 4Dorigo M,Gambardella L M,Middendorf M,et al. Guest editorial: special section on ant colony optimization[A]. IEEE Transactions on Evolutionary Computation[C]. 2002,6(4): 317-319. 被引量:1
  • 5Dorigo M,Dicaro G. Ant colony optimization: a new meta-heuristic[A]. Proceedings of the 1999 Congress on Evolutionary Computation[C]. Washington,DC,USA: 1999,Vol.2. 1477. 474-477. 被引量:1
  • 6Wang C M,Soh Y C,Wang H,et al. A hierarchical genetic algorithm for path planning in a static environment with obstacles[A]. IEEE CCECE Canadian Conference on Electrical and Computer Engineering[C]. 2002,vol.3.1652-1657. 被引量:1
  • 7D'Amico A,Ippoliti G,Longhi S A. Radial basis function networks approach for the tracking problem of mobile robots[A]. Proceedings of the IEEE/ASME. International Conference on Advanced Intelligent Mechatronics[C]. 2001,vol.1. 498-503. 被引量:1
  • 8Weerayuth N,Chaiyaratana N.Closed-loop time-optimal path planning using a multi-objective diversity control oriented genetic algorithm[A]. Systems,Man and Cybernetics[C]. IEEE International Conference on,Vol.6:7. 被引量:1
  • 9Bruce J,Veloso M. Real-time randomized path planning for robot navigation[A]. Intelligent Robots and Systems 2002. IEEE/RSJ International Conference on,2002,Vol.3. 2383- 2388. 被引量:1
  • 10Dorigo M,Maniezzo V,Colorni A. Ant system: optimization by a colony of cooperating agents[J]. IEEE Transactions on Systems ,Man and Cybernetics,Part B: Cybernetics,1996,26(1): 29-41. 被引量:1

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