This paper proposes a method for estimating the health status of spacecraft key components based on the belief rule base (BRB), a semi-quantitative method which uses both human judgmental information and numerical data. It not only allows experts to establish rules to provide useful conclusions, but also allows historical data to train its parameters to obtain more accurate outputs. To balance the parameter training and experts' knowledge, the Markov Chain Monte Carlo (MCMC) technique instead of traditional optimization method is used to adjust the BRB parameter. A practical case of estimating the health condition of space application batteries is studied.

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