An integrated deep multiscale feature fusion network for aeroengine remaining useful life prediction with multisensor data

2021 ◽  
pp. 107652
Author(s):  
Xingqiu Li ◽  
Hongkai Jiang ◽  
Yuan Liu ◽  
Tongqing Wang ◽  
Zhenning Li
2010 ◽  
Vol 450 ◽  
pp. 544-547
Author(s):  
Ji Hong Yan ◽  
Chao Zhong Guo ◽  
Xing Wang ◽  
De Bin Zhao

This paper proposed a neural network (NN) based remaining useful life (RUL) prediction approach. A new performance degradation index is designed using multi-feature fusion techniques to represent deterioration severities of facilities. Based on this indicator, back propagation neural networks are trained for RUL prediction, and average of the networks’ outputs is considered as the final RUL in order to overcome prediction errors caused by random initiations of NNs. Finally, an experiment is set up based on a Bently-RK4 rotor unbalance test bed to validate the neural network based life prediction models, experimental results illustrate the effectiveness of the methodology.


2005 ◽  
Vol 48 (2) ◽  
pp. 208-217 ◽  
Author(s):  
Matthew Watson ◽  
Carl Byington ◽  
Douglas Edwards ◽  
Sanket Amin

IEEE Access ◽  
2021 ◽  
pp. 1-1
Author(s):  
Bincheng Wen ◽  
Mingqing Xiao ◽  
Guanghao Wang ◽  
Zhao Yang ◽  
Jianfeng Li ◽  
...  

Author(s):  
Yu Zang ◽  
Wei Shangguan ◽  
Baigen Cai ◽  
Huasheng Wang ◽  
Michael. G. Pecht

Sign in / Sign up

Export Citation Format

Share Document