航天器工程2024，Vol.33Issue(2)：76-83,8.DOI:10.3969/j.issn.1673-8748.2024.02.012
基于VAE-DRSN的微纳卫星推力器故障诊断方法
Fault Diagnosis Method for Micro-nano Satellite Thruster Based on VAE-DRSN
朱劲锟 1郑侃 1梁振华 1唐嘉程1
作者信息
- 1. 南京理工大学 机械工程学院,南京 210094
- 折叠
摘要
Abstract
Aiming at the problem of fault diagnosis for micro-nano satellite thrusters,a data-driv-en propulsion system fault diagnosis method based on variational autoencoder-deep residual shrinkage network(VAE-DRSN)is proposed in this paper.This method uses a variational au-toencoder to extract the features from attitude data and controller output,and the extracted fea-tures are classified through a deep residual shrinkage neural network.It can accurately detect,di-agnose and locate the stuck on/off and make efficiency reduction faults of thrusters online,with-out the need for satellite thruster model and dynamic model,and without the need for separate hardware measurement mechanism.The numerical simulation results show that the accuracy of this method for single nozzle fault detection can reach over 99%,and it has good ability for thruster fault location and diagnosis.关键词
微纳卫星/故障诊断/深度学习/变分自编码器/推力器故障Key words
micro-nano satellite/fault diagnosis/deep learning/variational autoencoder/thruster fault分类
航空航天引用本文复制引用
朱劲锟,郑侃,梁振华,唐嘉程..基于VAE-DRSN的微纳卫星推力器故障诊断方法[J].航天器工程,2024,33(2):76-83,8.
