A Health State Prediction Model for Aeroengine Based on Multi-attribute Belief Rule Base with Considering Monitoring Error

Yin, Xiaojing; He, Qiangqiang; Peng, Shouxin; Chen, Dianxin; Zhang, Huiyong; Zhang, Bangcheng

doi:10.1007/s40815-024-01808-x

Int. J. Fuzzy Syst.

2024

DOI: 10.1007/s40815-024-01808-x

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A Health State Prediction Model for Aeroengine Based on Multi-attribute Belief Rule Base with Considering Monitoring Error

Xiaojing Yin,

Qiangqiang He,

Shouxin Peng

et al.

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Aerospace Equipment Fault Diagnosis Method Based on Fuzzy Fault Tree Analysis and Interpretable Interval Belief Rule Base

Long,

Zhu,

Zhang

et al. 2024

Mathematics

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The stable operation of aerospace equipment is important for space safety, and the fault diagnosis of aerospace equipment is of practical significance. A fault diagnosis system needs to establish clear causal relationships and provide interpretable determination results. Fuzzy fault tree analysis (FFTA) is a flexible and powerful fault diagnosis method, which can deeply understand causes and fault mechanisms. The interval belief rule base (IBRB) can describe uncertainty. In this paper, an interpretable fault diagnosis model (FFDI) for aerospace equipment based on FFTA and the IBRB is presented for the first time. Firstly, the initial FFDI is constructed with the assistance of FFTA. Second, a model inference is implemented based on an evidential reasoning (ER) parsing algorithm. Then, a projection covariance matrix adaptive evolutionary strategy algorithm with an interpretability constraints (IP-CMA-ES) optimization algorithm is used for optimization. Finally, the effectiveness of the FFDI is verified by a flywheel dataset. This method ensures the completeness of the rule base and the interpretability of the model, avoids the problem of exploding certain combinations of rules, and is suitable for the fault diagnosis of aerospace equipment.

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Aerospace Equipment Fault Diagnosis Method Based on Fuzzy Fault Tree Analysis and Interpretable Interval Belief Rule Base

Long,

Zhu,

Zhang

et al. 2024

Mathematics

View full text Add to dashboard Cite

show abstract

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A Health State Prediction Model for Aeroengine Based on Multi-attribute Belief Rule Base with Considering Monitoring Error

Cited by 1 publication

References 42 publications

Aerospace Equipment Fault Diagnosis Method Based on Fuzzy Fault Tree Analysis and Interpretable Interval Belief Rule Base

Aerospace Equipment Fault Diagnosis Method Based on Fuzzy Fault Tree Analysis and Interpretable Interval Belief Rule Base

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