航空学报 > 2020, Vol. 41 Issue (7): 323696-323696   doi: 10.7527/S1000-6893.2020.23696

基于可靠性分析的立方星网络维护架构优化

符弘岚1,2, 张皓1, 高扬1   

  1. 1. 中国科学院 空间应用工程与技术中心, 北京 100094;
    2. 中国科学院大学 计算机与控制学院, 北京 100049
  • 收稿日期:2019-12-04 修回日期:2020-01-02 出版日期:2020-07-15 发布日期:2020-02-06
  • 通讯作者: 张皓 E-mail:hao.zhang.zhr@gmail.com
  • 基金资助:
    国家重点研发计划(2018YFB1900605);中国科学院重点部署项目(ZDRW-KT-2019-1-0102)

Maintenance architecture optimization of CubeSat networks based on reliability analysis

FU Honglan1,2, ZHANG Hao1, GAO Yang1   

  1. 1. Technology and Engineering Center for Space Utilization, Chinese Academy of Sciences, Beijing 100094, China;
    2. School of Computer and Control Engineering, University of Chinese Academy of Sciences, Beijing 100049, China
  • Received:2019-12-04 Revised:2020-01-02 Online:2020-07-15 Published:2020-02-06
  • Supported by:
    National Key R&D Program of China (2018YFB1900605); Key Research Program of the Chinese Academy of Sciences(CAS) (ZDRW-KT-2019-1-0102)

摘要: 立方星编队或星座构成分布式空间传感器网络,可提高立方星执行复杂空间任务的能力。然而立方星易发生故障,其故障时间不确定性也导致了传感器网络性能的不稳定,这凸显了对立方星网络进行在轨维护的重要性。考虑立方星传感器网络的功能维持问题,描述了一种网络维护架构,通过定期发射、在轨备份立方星以及时更换故障立方星,从而提高网络对单星随机失效事件的快速响应与恢复能力。建立了该架构的运行成本模型,包括固定成本、储存成本和短缺成本。收集整理了真实的立方星寿命数据,并使用最大化拟合优度参数估计方法得到最优立方星寿命的随机模型。采用基于蒙特卡罗仿真的遗传算法优化备用立方星的补给时刻和补给数量,在备份成本与系统性能下降所带来的损失之间进行权衡,使得系统的综合收益最优。

关键词: 立方星失效故障数据, 空间传感器网络, 在轨维护架构, 在轨服务, Weibull分布

Abstract: CubeSat formations or constellations can form distributed space sensor networks, enhancing the ability of the CubeSat to execute sophisticated space missions. However, CubeSats are prone to malfunction, and the uncertainty of their failure time causes the performance instability of the sensor network, highlighting the importance of on-orbit maintenance of CubeSat networks. In view of the function maintenance of space CubeSat sensor networks, a maintenance architecture is described. It can improve the rapid responsiveness and recovery capability to a single CubeSat fault event of the network by launching CubeSats regularly, making backup CubeSats on the orbit and replacing damaged CubeSats in time. The operation cost model of this architecture is built, involving fixed costs, storage costs and shortage costs. The practical CubeSat lifetime data is collected to acquire the optimal CubeSat lifetime stochastic model with the parameter estimation optimization method of maximizing the coefficient of determination. The supply time and quantity of spare CubeSats are optimized by a Monte-Carlo-simulation-based genetic algorithm. This solution is a trade-off between the costs of backups and the losses caused by the system performance decline, finally achieving an optimal comprehensive income.

Key words: CubeSat failure data, space sensor networks, on-orbit maintenance architecture, on-orbit service, Weibull distribution

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