Satellite networking is a major trend in the future development of spaceflight,and to ensure the safe,reli-able and stable operation of many satellites in orbit,a single satellite is required to have high-precision in-orbit au-tonomous fault diagnosis capability.In this paper,for the characteristics of closed-loop fault propagation and high data dimensionality of the spacecraft control system,combined with the ground test data of a spacecraft,we first process the high-dimensional coupled sequence data to realize the mapping from sequence to grayscale image,and then use the convolution neural network(CNN)to complete the fault diagnosis of the same faulty component with high accuracy.The effectiveness of the proposed method is illustrated by comparing and validating it with non-im-age-based machine learning algorithms such as the K-neighborhood algorithm and the K-neighborhood algorithm based on principal component analysis.
维普
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