基于数据的在轨卫星太阳阵功率异常检测模型

Guoyong Zhang, Jun Zhou, Fengning Han, Datong Liu
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引用次数: 3

摘要

针对在轨卫星不可预测的故障,提出了一种基于正常历史遥测数据的数据异常检测方法,利用实时遥测数据检测在轨异常。首先,基于卫星太阳阵与太阳角计之间的关系,建立了太阳阵电流预测模型;此外,还采用了虚警过滤策略来降低虚警率。最后,将该模型应用于一个在轨卫星故障案例,实验结果表明,该方法能够及时、准确地识别太阳电池阵输出故障,且具有较小的时间延迟。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Data-based anomaly detection model for solar array power of in-orbit satellites
For unpredictable failures of in-orbit satellites, a data-based anomaly detection method, which is based on normal historical telemetry data, is proposed to detect in-orbit anomaly with the real-time telemetry data. Firstly, a solar array current prediction model is constructed based on the relationship between the satellite solar array and the sun angle meter. Moreover, a false alarm filtering strategy is applied to reduce the false alarm rate. Finally, the model is used in an in-orbit satellite failure case, and the experimental results indicate that the proposed method can timely and accurately identify the solar array output failure with little time delay.
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