A Working Pattern Recognition Method For Satellite Power System Based On Uncertain Data Clustering Strategy

Xiaozhen Yan, Qinghua Luo, Yipeng Yang, Zhuo Yang
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引用次数: 1

Abstract

The power system plays a major role in the maintenance of working properly for satellite. As there are many working loads and different working attitudes, the power system has many diverse working patterns. So it is very critical to recognize the working patterns accurately. However, due to the measurement error, environmental interference, and other uncertainty factors, the output voltage of the satellite power system has remarkable uncertainty. If we did not consider the uncertainty and various working patterns, poor recognized result will be generated. For this issue, we proposed a working patterns recognition method for satellite power system based on uncertainty data clustering strategy. In this method, we firstly utilize uncertainty data clustering strategy to modeling working patterns. Then during pattern recognition stage, we calculate the distances between uncertain cluster centers and the measurement data. The experimental results of actual power system data illustrate the validation and feasibility of our proposed method.
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基于不确定数据聚类策略的卫星电力系统工作模式识别方法
电力系统对卫星的正常运行起着重要的维护作用。由于电力系统有多种工作负荷和不同的工作态度,因此电力系统具有多种多样的工作模式。因此,准确识别其工作模式至关重要。然而,由于测量误差、环境干扰等不确定因素的影响,卫星电力系统的输出电压具有显著的不确定性。如果不考虑不确定性和各种工作模式,就会产生较差的识别结果。针对这一问题,提出了一种基于不确定性数据聚类策略的卫星电力系统工作模式识别方法。该方法首先利用不确定性数据聚类策略对工作模式进行建模。然后在模式识别阶段,计算不确定聚类中心与测量数据之间的距离。实际电力系统数据的实验结果验证了该方法的有效性和可行性。
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