ABCLS method for high-reliability aerospace mechanism with truncated random uncertainties  

作　　者：Peng Wensheng Zhang Jianguo Zhu Dantong 

机构地区：[1]School of Reliability and Systems Engineering, Beihang University [2]Science and Technology on Reliability and Environment Engineering Laboratory, Beihang University

出　　处：《Chinese Journal of Aeronautics》2015年第4期1066-1075,共10页中国航空学报（英文版）

基　　金：supported by the National Basic Research Program of China (No.2013CB733002)

摘　　要：The random variables are always truncated in aerospace engineering and the truncated distribution is more feasible and effective for the random variables due to the limited samples available.For high-reliability aerospace mechanism with truncated random variables, a method based on artificial bee colony（ABC） algorithm and line sampling（LS） is proposed.The artificial bee colony-based line sampling（ABCLS） method presents a multi-constrained optimization model to solve the potential non-convergence problem when calculating design point（is also as most probable point, MPP） of performance function with truncated variables; by implementing ABC algorithm to search for MPP in the standard normal space, the optimization efficiency and global searching ability are increased with this method dramatically.When calculating the reliability of aerospace mechanism with too small failure probability, the Monte Carlo simulation method needs too large sample size.The ABCLS method could overcome this drawback.For reliability problems with implicit functions, this paper combines the ABCLS with Kriging response surface method,therefore could alleviate computational burden of calculating the reliability of complex aerospace mechanism.A numerical example and an engineering example are carried out to verify this method and prove the applicability.The random variables are always truncated in aerospace engineering and the truncated distribution is more feasible and effective for the random variables due to the limited samples available.For high-reliability aerospace mechanism with truncated random variables, a method based on artificial bee colony（ABC） algorithm and line sampling（LS） is proposed.The artificial bee colony-based line sampling（ABCLS） method presents a multi-constrained optimization model to solve the potential non-convergence problem when calculating design point（is also as most probable point, MPP） of performance function with truncated variables; by implementing ABC algorithm to search for MPP in the standard normal space, the optimization efficiency and global searching ability are increased with this method dramatically.When calculating the reliability of aerospace mechanism with too small failure probability, the Monte Carlo simulation method needs too large sample size.The ABCLS method could overcome this drawback.For reliability problems with implicit functions, this paper combines the ABCLS with Kriging response surface method,therefore could alleviate computational burden of calculating the reliability of complex aerospace mechanism.A numerical example and an engineering example are carried out to verify this method and prove the applicability.

关 键 词：Artificial bee colony algo-rithm High reliability Kriging model Line sampling Truncated random variables 

分 类 号：V415[航空宇航科学与技术—航空宇航推进理论与工程]