Tang Yongchuan, Zhou Yonghao, Zhou Ying, Huang Yubo, Zhou Deyun
School of Microelectronics, Northwestern Polytechnical University, Xi'an 710072, China.
School of Computer Science, Northwestern Polytechnical University, Xi'an 710072, China.
Entropy (Basel). 2023 May 6;25(5):757. doi: 10.3390/e25050757.
Failure mode and effects analysis (FMEA) is a proactive risk management approach. Risk management under uncertainty with the FMEA method has attracted a lot of attention. The Dempster-Shafer (D-S) evidence theory is a popular approximate reasoning theory for addressing uncertain information and it can be adopted in FMEA for uncertain information processing because of its flexibility and superiority in coping with uncertain and subjective assessments. The assessments coming from FMEA experts may include highly conflicting evidence for information fusion in the framework of D-S evidence theory. Therefore, in this paper, we propose an improved FMEA method based on the Gaussian model and D-S evidence theory to handle the subjective assessments of FMEA experts and apply it to deal with FMEA in the air system of an aero turbofan engine. First, we define three kinds of generalized scaling by Gaussian distribution characteristics to deal with potential highly conflicting evidence in the assessments. Then, we fuse expert assessments with the Dempster combination rule. Finally, we obtain the risk priority number to rank the risk level of the FMEA items. The experimental results show that the method is effective and reasonable in dealing with risk analysis in the air system of an aero turbofan engine.
失效模式与影响分析(FMEA)是一种主动的风险管理方法。采用FMEA方法在不确定性条件下进行风险管理已引起广泛关注。Dempster-Shafer(D-S)证据理论是一种用于处理不确定信息的流行近似推理理论,因其在处理不确定和主观评估方面的灵活性和优越性,可应用于FMEA中的不确定信息处理。来自FMEA专家的评估可能在D-S证据理论框架下包含高度冲突的信息融合证据。因此,本文提出一种基于高斯模型和D-S证据理论的改进FMEA方法,以处理FMEA专家的主观评估,并将其应用于航空涡轮风扇发动机空气系统的FMEA中。首先,通过高斯分布特征定义三种广义标度,以处理评估中潜在的高度冲突证据。然后,利用Dempster组合规则融合专家评估。最后,得到风险优先数,对FMEA项目的风险水平进行排序。实验结果表明,该方法在处理航空涡轮风扇发动机空气系统风险分析时有效且合理。