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Fault detection and reconstruction for micro-satellite power subsystem based on PCA

机译:基于PCA的微卫星电源子系统故障检测与重构

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Fault detection and reconstruction for micro-satellite power subsystem was achieved by using the principal component analysis (PCA) method. Four typical kinds of sensor failure were identified. The principle to establish the PCA model, diagnose and reconstruct faulty sensors was presented. A model of a satellite's power subsystem, which is consisted of voltage, temperature, and current parameters, was introduced. Using the normal data acquired from the experiment, we established the approximate PCA model for the satellite power system. With the incorrect data introduced to simulate the sensor failure occurrence, the value of squared prediction error (SPE) and sensor validity index (SVI) was detected beyond the confidence limit. Subsequently, the faulty sensor was isolated and reconstructed. The simulation results indicated that the PCA method was probably effective for fault detection and reconstruction in satellite power subsystem.
机译:利用主成分分析(PCA)方法实现了微卫星电源子系统的故障检测与重构。确定了四种典型的传感器故障。提出了建立PCA模型,诊断和重建故障传感器的原理。介绍了由电压,温度和电流参数组成的卫星功率子系统模型。使用从实验中获得的正常数据,我们建立了卫星电源系统的近似PCA模型。通过引入不正确的数据来模拟传感器故障的发生,检测出的平方预测误差(SPE)和传感器有效性指标(SVI)的值超出了置信度限制。随后,隔离并重建了故障传感器。仿真结果表明,PCA方法可能对卫星电力子系统的故障检测和重构是有效的。

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