航天器泵驱单相流体回路在轨数据分析及预测OA

To address the problem that data directly acquired from single-phase fluid loops in spacecraft thermal control systems contain substantial white noise and exhibit severe fluctua-tions,which makes it difficult to directly extract effective information,a three-stage on-orbit data processing method based on Hurst-exponent-driven time-series decomposition,filtering and pre-diction is proposed in this paper.Hurst exponents are used to quantify the characteristics of the data.Time-series decomposition is the performed to separate the trend,periodic,and residual components.Fourier transform-based filtering is applied to attenuate white noise and discrete ab-rupt variations.An adjustable fractional-order integration model is then constructed fpr future trend prediction.Analysis of on-orbit data indicates that spacecraft thermal control data exhibits periodic fluctuations due to temperature variation cycles induced by orbital motion.The pump ro-tational speed demonstrates strong mean-reverting characteristics,while the liquid level shows a linear leakage trend,with an annual leakage rate of approximately 0.6mm.In addition,a high-confidence linear relationship is observed between pressure and liquid level.This method provides support for the safe on-orbit operation of spacecraft thermal control systems.