Reliability analysis of nozzle adjustment mechanism with interval distribution parameters

被引：0
|
作者：
Zhang Z. [1 ]
Wang P. [1 ]
Zhou H. [2 ]
机构：
[1] School of Mechanics, Civil Engineering and Architecture, Northwestern Polytechnical University, Xi’an
[2] Xi’an Aerospace Propulsion Institute, Xi’an
来源：
Beijing Hangkong Hangtian Daxue Xuebao/Journal of Beijing University of Aeronautics and Astronautics | 2023年 / 49卷 / 12期
基金：
中国国家自然科学基金;
关键词：
adjustment mechanism; interval distribution parameter; Kriging surrogate model; rejection sampling; reliability;
D O I：
10.13700/j.bh.1001-5965.2022.0089
中图分类号：
学科分类号：
摘要：
To improve the reliability analysis efficiency of the engine nozzle adjustment mechanism, an analysis method combining rejection sampling and active learning Kriging surrogate model is proposed. A virtual prototype simulation model of an engine nozzle adjustment mechanism was established in ADAMS, and the established model is verified by kinematics analysis. Considering the situation that its input variables contain interval distribution parameters, a limit state function based on the positioning accuracy of the adjusting mechanism is established. When distribution parameters change at random, the rejection sampling approach captures the changes in the sample space in order to build a Kriging surrogate model that is appropriate for the full sample space. A numerical example that validates the viability of the suggested approach is used to calculate and analyze the upper and lower boundaries of the adjustment mechanism failure probability. It provides a new method to improve the reliability analysis efficiency under interval distributed parameters. © 2023 Beijing University of Aeronautics and Astronautics (BUAA). All rights reserved.
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页码：3377 / 3385
页数：8
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