基于贝叶斯灵敏度函数的卫星姿控系统节点优选

Node Selection of Satellite Attitude Control System Based on Sensitivity Function in Bayesian Network

为了提高卫星姿控系统在轨故障诊断的效率,节约星上有限的存储空间,本文研究了基于贝叶斯灵敏度函数的卫星姿控系统节点优选问题。首先,在历史故障数据及专家经验的基础上建立了卫星姿控系统的贝叶斯网络模型,避免故障的复杂性与不确定性对系统的影响。然后,应用贝叶斯灵敏度函数分析节点重要度,提出系统节点优选算法。其有助于系统的可靠性设计与故障诊断。最后,通过计算结果分析了该方法的有效性与实际应用价值。

In order to improve efficiency of on-orbit fault diagnosis of satellite attitude control system and save limited storage space, the node selection problem of satellite attitude control system based on the sensitivity function in Bayesian Network is investigated. First, the Bayesian network model of satellite attitude control system is established based on expert experience and historical failure data to reduce the influence of the fault complexity and uncertainty on system. Then, through analyzing the node importance, the node selection algorithm is proposed by using the Bayesian sensitivity function, which contributes to reliability design and fault diagnosis of the system. Finally, numerical computation results show that the proposed algorithm is efficient and has the potential to be used in practice.