Autonomous Recommendation of Fault Detection Algorithms for Spacecraft

Abstract

Dear Editor, This letter deals with the problem of algorithm recommendation for online fault detection of spacecraft. By transforming the time series data into distributions and introducing a distribution-aware measure, a principal method is designed for quantifying the detectabilities of fault detection algorithms over special datasets. Based on a sublinear time filtering method, an efficient algorithm for evaluating the detectabilities is designed. By combining the above techniques, RecAD is proposed for the recommendation of fault detection algorithms. Experimental results over typical datasets show that RecAD can select the detecting algorithm with better performance efficiently and the cost of the recommendation is rather small.