MBRB: Micro-belief rule Base model based on cautious conjunctive rule for interpretable fault diagnosis

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—In aerospace engineering, implementing interpretable fault diagnosis technology is critical for improving the credibility of diagnostic results and ensuring the reliability of complex electromechanical systems. As a typical interpretable modeling method, the belief rule base (BRB) approach still faces two challenges that need to be addressed for its application in interpretable fault diagnosis: 1) The lengthy rule structures raise the cost of model interpretability, and 2) over-optimization of parameters diminishes the interpretability. To solve these problems, this paper proposes a modified micro-belief rule structure and develops a new micro-belief rule base (MBRB) model based on this structure. In addition, considering the independence of rules and the correlations between multiple BRBs, a cautious conjunctive rule-based reasoning process is established as the inference engine of MBRB. Moreover, an interpretable optimization method based on projection covariance matrix adaptive evolutionary strategy (PCMAES-I) is proposed for the MBRB model to balance model interpretability and diagnostic accuracy. Finally, the availability and effectiveness of the proposed MBRB is verified through an electromagnetic relay experiment.