航空发动机限寿件疲劳可靠度计算新方法

doi:10.7527/S1000-6893.2019.23228

Abstract

Abstract: Aiming at the small failure probability events and the strong non-linearity of limit state function in the fatigue reliability analysis of aero-engine Limited Life Parts (ELLP), a fatigue reliability analysis method based on the Auto Updating Monte Carlo Radius-Outside Adaptive Importance Sampling (AUMCROAIS) is proposed. In this method, the Monte Carlo Adaptive Importance Sampling (MCAIS) is used to approach the Most Probable Point (MPP) efficiently, then the polar coordinate sampling is employed by taking the approximate MPP as the sampling center. An active learning function is constructed to optimize the near-limit state function and sampling radius, so that the optimal sampling radius can be updated. The optimal sampling radius can be determined through continuous updating, accelerating the convergence of failure probability. This method improves the convergence speed of MPP points and ensures the accuracy of calculation. It solves the problem of reliability calculation of small failure probability events and strong non-linear limit state function. Finally, taking a compressor disk of an engine as an application, and the efficiency, robustness and simulation accuracy of the proposed method are verified by comparing with the traditional Monte Carlo Simulation (MCS) method, the Monte Carlo Radius-Outside Adaptive Importance Sampling (MCROAIS), and First-Order Reliability Method (FORM).

Key words: fatigue reliability, aero-engine, adaptive importance sampling, automatic updating, active learning

CLC Number:

YOU Lingfei, ZHANG Jianguo, ZHOU Shuang, DU Xiaosong. A new method for fatigue reliability calculation of aero-engine limited life parts[J]. ACTA AERONAUTICAET ASTRONAUTICA SINICA, 2019, 40(12): 223228-223228.

References 26

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A new method for fatigue reliability calculation of aero-engine limited life parts

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