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Fault diagnosis for space utilisation.

Authors :
Sun, Yuanyuan
Guo, Lili
Wang, Yongming
Ma, Zhongsong
Niu, Yi
Source :
Journal of Engineering; Dec2019, Vol. 2019 Issue 12, p8770-8775, 6p
Publication Year :
2019

Abstract

The space application task is to carry out various scientific experiments and applied research by using the ability of space experiment of spacecraft. In the past 20 years, >50 space application studies have been carried out in Chinese manned space flight application system, >500 units have been involved in the previous flight missions, and fruitful results have been achieved. The white paper 'Chinese spaceflight in 2016' pointed out that in the next 5 years, Chinese satellite system will enhance the level and basic ability to construct the satellite system. Chinese manned space station project is scheduled to be completed ∼2022 and it will plan to operate >10 years. The space station, based on the world-wide integrated information network, has a large number of payloads and will become a national space laboratory. Space activities are full of risks and challenges. On the basis of a great deal of literatures, the method of avoiding space risk in the field of spaceflight is discussed. Aiming at the fault diagnosis task for space utilisation, the intelligent methods of deep learning including deep belief network, convolutional neural network and generative adversarial network are discussed. [ABSTRACT FROM AUTHOR]

Details

Language :
English
ISSN :
20513305
Volume :
2019
Issue :
12
Database :
Complementary Index
Journal :
Journal of Engineering
Publication Type :
Academic Journal
Accession number :
148149495
Full Text :
https://doi.org/10.1049/joe.2018.9102