Weighted Fuzzy Risk Priority Number Evaluation of Turbine and Compressor Blades Considering Failure Mode Correlations

Abstract

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 correla tions 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 epis temic 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 pro babilities of each MCS. Compared to the case where de pendency among multiple failure modes is not consid ered, the Copula modeling approach eliminates the error of reliability analysis. Furthermore, for purpose of quan titative analysis, probabilities importance weight from failure probabilities are assigned to FWGM RPN to reas sess 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 com pressor blades in aeroengine 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 struc tural system under failure correlations.

Fatigue reliability and sensitivity analysis of aero‐disk considering correlation

“…When the hazardous regions are completely related, the reliabilities from MCS and AK-MCS are 0.999908 and 0.999912. Comparing the calculation results, they are consistent with Equation (30), so it can be judged that the calculating results are reasonable.…”

“…29 Gan et al integrated the advantages of fuzzy theory, and Copula theory into a unified hybrid method. 30 By eliminating errors in reliability analysis using Copula functions, they achieved fatigue reliability analysis of turbine compressor. Li et al proposed a copula-based reliability modeling approach to capture component dependencies in phased mission systems across multiple phases.…”

“…Gan et al. integrated the advantages of fuzzy theory, and Copula theory into a unified hybrid method 30 . By eliminating errors in reliability analysis using Copula functions, they achieved fatigue reliability analysis of turbine compressor.…”

Fatigue reliability analysis of crack growth life using maximum entropy method

“…Fatigue fracture failure is one of the main failure modes for aero engine components under cyclic loadings. [1][2][3][4][5][6] Fatigue life usually consists of crack initiation life and crack growth life, and as an important performance index, fatigue crack growth life must be taken into account in damage tolerance design for aero engine components. 7,8 As the key parts of the aero engine, damage tolerance design for turbine disk plays an important role on improving the structural fatigue reliability and ensuring the safety during the service life.…”