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首页> 外文期刊>International Journal of Turbo and Jet Engines >Weighted Fuzzy Risk Priority Number Evaluation of Turbine and Compressor Blades Considering Failure Mode Correlations
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Weighted Fuzzy Risk Priority Number Evaluation of Turbine and Compressor Blades Considering Failure Mode Correlations

机译:考虑失效模式相关性的汽轮机和压气机叶片加权模糊风险优先级评估

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摘要

Failure mode, effects and criticality analysis (FMECA) and Fault tree analysis (FTA) are powerful tools to evaluate reliability of systems. Although single failure mode issue can be efficiently addressed by traditional FMECA, multiple failure modes and component correlations in complex systems cannot be effectively evaluated. In addition, correlated variables and parameters are often assumed to be precisely known in quantitative analysis. In fact, due to the lack of information, epistemic uncertainty commonly exists in engineering design. To solve these problems, the advantages of FMECA, FTA, fuzzy theory, and Copula theory are integrated into a unified hybrid method called fuzzy probability weighted geometric mean (FPWGM) risk priority number (RPN) method. The epistemic uncertainty of risk variables and parameters are characterized by fuzzy number to obtain fuzzy weighted geometric mean (FWGM) RPN for single failure mode. Multiple failure modes are connected using minimum cut sets (MCS), and Boolean logic is used to combine fuzzy risk priority number (FRPN) of each MCS. Moreover, Copula theory is applied to analyze the correlation of multiple failure modes in order to derive the failure probabilities of each MCS. Compared to the case where dependency among multiple failure modes is not considered, the Copula modeling approach eliminates the error of reliability analysis. Furthermore, for purpose of quantitative analysis, probabilities importance weight from failure probabilities are assigned to FWGM RPN to reassess the risk priority, which generalize the definition of probability weight and FRPN, resulting in a more accurate estimation than that of the traditional models. Finally, a basic fatigue analysis case drawn from turbine and compressor blades in aero-engine is used to demonstrate the effectiveness and robustness of the presented method. The result provides some important insights on fatigue reliability analysis and risk priority assessment of structural system under failure correlations.
机译:故障模式,影响和临界度分析(FMECA)和故障树分析(FTA)是评估系统可靠性的强大工具。尽管传统的FMECA可以有效地解决单个故障模式问题,但是不能有效地评估复杂系统中的多个故障模式和组件相关性。另外,在定量分析中通常假定相关变量和参数是精确已知的。实际上,由于缺乏信息,工程设计中普遍存在认识不确定性。为了解决这些问题,将FMECA,FTA,模糊理论和Copula理论的优点集成到称为模糊概率加权几何平均值(FPWGM)风险优先级数(RPN)方法的统一混合方法中。通过模糊数对风险变量和参数的认知不确定性进行表征,以获得单故障模式的模糊加权几何平均数(FWGM)RPN。使用最小割集(MCS)连接多个故障模式,并使用布尔逻辑组合每个MCS的模糊风险优先级数字(FRPN)。此外,应用Copula理论分析多种失效模式之间的相关性,以推导每个MCS的失效概率。与不考虑多个故障模式之间的依赖性的情况相比,Copula建模方法消除了可靠性分析的错误。此外,出于定量分析的目的,将故障概率中的概率重要性权重分配给FWGM RPN,以重新评估风险优先级,从而归纳了概率权重和FRPN的定义,从而得出比传统模型更准确的估计。最后,从航空发动机的涡轮和压缩机叶片得出的基本疲劳分析案例被用来证明所提出方法的有效性和鲁棒性。该结果为失效相关性下结构系统的疲劳可靠性分析和风险优先级评估提供了重要的见识。

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