利用随机森林算法的卫星控制系统故障诊断

Fault Diagnosis of Satellite Attitude Control Systems Using Random Forest Algorithm

针对卫星姿态控制系统存在闭环控制,外部干扰强,进而影响故障诊断准确性和实时性的问题,提出了一种利用随机森林算法的卫星姿态控制系统姿态敏感器和执行器故障诊断方法。首先,采集不同故障情形下卫星姿态控制系统的输入输出数据,进行特征提取。随后通过随机有放回抽样划分训练集和测试集,建立基于随机森林算法的故障诊断模型。利用生成的随机森林模型,对实时输入输出数据进行分类,实现卫星姿态控制系统的故障诊断。利用卫星姿态控制系统半物理仿真平台的数据进行实验,对比实验结果表明:本文所提方法可以实现故障高精度分离,并具有更好的实时性,适用于卫星姿态控制系统的故障诊断问题。

To cope with the closed-loop controls and strong external disturbances,a fault diagnosis method based on the random forest(RF)algorithm is proposed for satellite attitude control systems.Firstly,various types of signals in satellite attitude control systems in different faulty scenarios are collected.Then,some characteristics of the data are extracted and a RF-based fault diagnosis model is established correspondingly.The possible faults can be diagnosed via injecting the real-time data into the obtained RF-based model.The effectiveness of the proposed method is illustrated on a semi-physical simulation platform,and the comparison results show that our approach can identify a variety of faults with high accuracy and efficiency.