Concurrent fault diagnosis method based on belief rule base

To solve the problem of concurrent fault diagnosis with uncertainty, a belief rule base (BRB) diagnosis method based on attribute weights and tradeoff analysis is proposed. In the proposed method, the attribute weights are used to represent the correlation between the attributes and the specific failure mode, and an optimization algorithm via differential evolution (DE) which can reflect fault model constraints is designed. The concurrency fault mode diagnosis is completed by the trade-off analysis between the adjacent fault mode belief and the preset threshold. This method only needs to construct a single BRB to effectively deal with various uncertainty information, which greatly reduces the modeling complexity compared with the existing research methods. The diagnosis results can not only get the concurrency of the faults but also distinguish the main fault and the minor fault. The modeling and reasoning process is open and interpretable. Finally, the concurrent fault diagnosis of a marine diesel engine is taken as an example and proves the proposed method can effectively diagnose the concurrent faults with good stability. © 2020, Editorial Office of Systems Engineering and Electronics. All right reserved.