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DLLE-EWMA based Incipient Fault Detection for Satellite Attitude Control System

机译:基于DLLE-EWMA的卫星姿态控制系统早期故障检测

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In this paper, an incipient fault detection (FD) method that is applied to satellite attitude control system (ACS), is proposed based on the locally linear embedding algorithm with dynamic neighborhood parameters (DLLE) and the exponentially weighted moving average (EWMA) strategy. Dynamic neighborhood parameter selection is introduced to LLE, so that the weight reconstruction matrix can be determined according to the sample density of the manifold. Then, the DLLE algorithm is integrated with EWMA in both the latent and residual subspaces to establish the EWMA-T2 and EWMA-SPE statistics for incipient fault detection. Case study is conducted using the real telemetry data from two on-orbit satellites, and the results can demonstrate the effectiveness and feasibility of this proposed incipient FD method.
机译:基于动态邻域参数(DLLE)的局部线性嵌入算法和指数加权移动平均(EWMA)策略,提出了一种应用于卫星姿态控制系统(ACS)的早期故障检测(FD)方法。 。将动态邻域参数选择引入到LLE中,以便可以根据歧管的样本密度确定权重重构矩阵。然后,将DLLE算法与EWMA在潜在子空间和残差子空间中进行集成,以建立EWMA-T 2 以及用于早期故障检测的EWMA-SPE统计信息。案例研究是使用来自两颗在轨卫星的真实遥测数据进行的,结果可以证明该提议的初始FD方法的有效性和可行性。

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