AEROSPACE SHANGHAI, Volume. 42, Issue 2, 49(2025)
Design of a Health Status Prediction System for Space Power-sources
[2] C L TAN, T B HU, P WANGD. Fault statistics and analysis of on-orbit fault of foreign spacecraft. Spacecraft Engineering, 20, 130-136(2011).
[3] S DHEEPADHARSHANI, S ANANDH, K B BHAVINAYA et al. Multivariate time-series classification for automated fault detection in satellite power systems(2019).
[4] H LI, J HE, X W WANG et al. Research review and prospect of fault diagnosis method of satellite power system based on machine learning(2018).
[30] S JENU, A HENTUNEN, J HAAVISTO et al. State of health estimation of cycle aged large format lithium-ion cells based on partial charging. Journal of Energy Storage, 46, 103855(2022).
[31] W A YANG, M H XIAO, W ZHOU et al. A hybrid prognostic approach for remaining useful life prediction of lithium-ion batteries. Shock and Vibration, 3838765(2016).
[32] G GIDAYE, J NIRMAL, K EZZINE et al. Wavelet sub-band features for voice disorder detection and classification. Multimedia Tools and Applications, 79, 28499-28523(2020).
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Wenjie LI, Baozhang YANG, Guoling CHEN. Design of a Health Status Prediction System for Space Power-sources[J]. AEROSPACE SHANGHAI, 2025, 42(2): 49
Category: Research and Application of Large Models
Received: Feb. 27, 2025
Accepted: --
Published Online: May. 26, 2025
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