Generalized Reliability Analysis of Mechanical Systems with Imperfect Maintenance

Generalized reliability models and failure rate models of mechanical systems are developed in this paper according to the system working mechanism, which take the design parameters as input. The models consider strength degradation and imperfect maintenance. Besides, the models take into account the failure correlation caused by homologous load effect and the maintenance correlation owing to group maintenance. Unlike traditional reliability models, the models do not rely on empirical assumptions when considering failure correlation and maintenance correlation and have clear physical meaning. Moreover, the correctness and effectiveness of the models are verified by Monte Carlo simulations. Finally, the influences of failure correlation and maintenance correlation on generalized reliability, the influences of failure correlation on maintenance correlation, and the influences of maintenance correlation on failure correlation are analyzed via numerical examples. The results show that failure correlation and maintenance correlation have great influences on generalized reliability, and the interaction between the two correlation shows obvious time-varying characteristics.

Reliability Analysis on Fatigue Life of Turbine Disk Regarding for the Correlation Between Divided Zones

Failure of a turbine disk may occur in multiple parts of the disk. It should be taken into consideration that during the process of failure, the failure risk of other relevant parts tend to increase due to the change of stress state of the disk. Therefore, the failure risks of different parts are related. This paper puts forward a reliability analysis method considering the failure correlation between different zones of the disk. Firstly, the dependence between the low cycle fatigue (LCF) of the whole turbine disk and the LCF of each zone is considered in building a multivariate reliability model based on Copula function theory. With utilizing the sample points obtained by finite element method (FEA), the multidimensional maximum likelihood theory is used to estimate the parameters in the marginal distribution of turbine disk life and the correlation coefficients in the Copula model, and to quantify the failure correlation between each zone of the turbine disk. With regard to the lifetime output of different zones, fourth-order polynomial high-precision surrogate models are established, which greatly improves the efficiency of Monte Carlo simulation. Eventually, the LCF life reliability analysis of GH720Li turbine disk is performed.