Digital twin for the structural health management of reusable spacecraft: A case study

被引:73
|
作者
Ye, Yumei [1 ]
Yang, Qiang [1 ,2 ]
Yang, Fan [1 ]
Huo, Yanyan [1 ]
Meng, Songhe [1 ]
机构
[1] Harbin Inst Technol, Natl Key Lab Sci & Technol Natl Def Adv Composite, Harbin 150001, Heilongjiang, Peoples R China
[2] Harbin Inst Technol, Postdoctoral Res Ctr Mat Sci & Engn, Harbin 150001, Heilongjiang, Peoples R China
基金
中国博士后科学基金; 中国国家自然科学基金;
关键词
KALMAN FILTER; PROGNOSTICS; STATE;
D O I
10.1016/j.engfracmech.2020.107076
中图分类号
O3 [力学];
学科分类号
08 ; 0801 ;
摘要
Reusable spacecraft can significantly reduce the cost of space travel, while evaluation of the structural health of the craft between flights becomes one of the key issues. A digital twin framework is proposed in this paper to track the life of spacecraft structures. A digital twin is a digital representation of an engineering system. It can simulate, monitor, diagnose, predict states and optimize operations of the real engineering system in real time. The proposed framework can be divided into offline and online stages. It has the functions of diagnosis, model updating, performance evaluation and data storage. To demonstrate the prognosis and decision support capabilities of the framework, a numerical example considering fatigue crack growth in a load-bearing frame is carried out. The method of manufactured solutions is employed for validation. Information entropy and relative entropy are used for measuring the uncertainties in crack length prediction. The results show that through the framework, crack growth model can be updated to have a lower uncertainty. Future crack growth and reusable life can be predicted more accurately using the improved model. With the structural life of the spacecraft quantified by the framework, mission success rates for repeated flights can be maximized at a lower cost. © 2020 Elsevier Ltd
引用
收藏
页数:16
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