可 靠 性 分 析 改 进 元 模 型 重 要 抽 样 算 法

To give an efficient analysis of structural reliability，an enhanced metamodel-based importance sampling method is proposed in this paper by introducing an error-based stopping criterion for updating the Kriging model. Firstly，an analytical relationship of the relative error between the estimate of failure probability by the metamodel-based importance sampling method and the true value obtained by the actual limit state function is established. Secondly，an approximate relationship between the upper bound of the relative error between the estimate of failure probability and the true value and the prediction accuracy of the Kriging model is derived. By ensuring that the relative error between the estimate of failure probability by the metamodel-based importance sampling method and the true value obtained by the actual limit state function does not exceed a predefined accuracy，an error-based stopping criterion for updating the Kriging model is established to improve the efficiency of the existing metamodel-based importance sampling method. Finally，the proposed method is applied to numerical examples and engineering examples of reliability analysis of turbine shaft fatigue life. The results verify the efficiency and accuracy of the proposed method.