Digital twin-assisted multiscale residual-self-attention feature fusion network for hypersonic flight vehicle fault diagnosis

Yutong Dong, Hongkai Jiang, Zhenghong Wu, Qiao Yang and Yunpeng Liu

Reliability Engineering and System Safety, 2023, vol. 235, issue C

Abstract: Hypersonic flight vehicle (HFV) with long term exposure to poor operating environments will inevitably experience performance degradation and potential failures. Currently, data-driven approaches have been commonly used for fault diagnosis. However, it is a challenge to obtain reliable and adequate data to identify HFV faults. To cope with this issue, this paper put forward a digital twin-assisted multiscale residual-self-attention feature fusion network (MRFFN) for hypersonic flight vehicle fault diagnosis. Firstly, a mathematical simulation is performed to establish the DT model of HFV. Then, the constructed DT model is employed for simulating multiple fault states of HFV to generate an approximation to the real system state data. Finally, a novel MRFFN is designed for training and validation utilizing the data derived from the DT model. The comparison performance demonstrates the MRFFN is superior to other intelligence methods in its ability to accurately identify hypersonic flight vehicle faults.

Keywords: Hypersonic flight vehicle; Fault diagnosis; Digital twin; Multiscale residual-self-attention feature fusion network (search for similar items in EconPapers)
Date: 2023
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (6)

Downloads: (external link)
http://www.sciencedirect.com/science/article/pii/S0951832023001680
Full text for ScienceDirect subscribers only

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:eee:reensy:v:235:y:2023:i:c:s0951832023001680

DOI: 10.1016/j.ress.2023.109253

Access Statistics for this article

Reliability Engineering and System Safety is currently edited by Carlos Guedes Soares

More articles in Reliability Engineering and System Safety from Elsevier
Bibliographic data for series maintained by Catherine Liu ().