Predicting remaining useful life of a machine based on embedded attention parallel networks-Reference-Cited by-同舟云学术

Predicting remaining useful life of a machine based on embedded attention parallel networks

Published:2023-06 Issue: Volume:192 Page:110221
ISSN:0888-3270
Container-title:Mechanical Systems and Signal Processing
language:en
Short-container-title:Mechanical Systems and Signal Processing

Author:

Zhang Xiong^ORCID,Guo Yunfei,Shangguan Hong,Li Ranran,Wu Xiaojia,Wang Anhong

Publisher

Elsevier BV

Subject

Computer Science Applications,Mechanical Engineering,Aerospace Engineering,Civil and Structural Engineering,Signal Processing,Control and Systems Engineering

Reference40 articles.

1. A classification framework for predicting components’ remaining useful life based on discrete-event diagnostic data;Fink;IEEE Trans. Reliab.,2015

2. Remaining useful life prediction of aircraft engine based on degradation pattern learning;Zhao;Reliab. Eng. Syst. Saf.,2017

3. Remaining useful life estimation in heterogeneous fleets working under variable operating conditions;Al-Dahidi;Reliab. Eng. Syst. Saf.,2016

4. State of the art and taxonomy of prognostics approaches, trends of prognostics applications and open issues towards maturity at different technology readiness levels;Javed;Mech. Syst. Sig. Process.,2017

5. A particle filtering and kernel smoothing-based approach for new design component prognostics;Hu;Reliab. Eng. Syst. Saf.,2015

Cited by 14 articles. 订阅此论文施引文献订阅此论文施引文献，注册后可以免费订阅5篇论文的施引文献，订阅后可以查看论文全部施引文献

1. MST-GAT: A multi-perspective spatial-temporal graph attention network for multi-sensor equipment remaining useful life prediction;Information Fusion;2024-10

2. Aircraft engine remaining useful life prediction: A comparison study of Kernel Adaptive Filtering architectures;Mechanical Systems and Signal Processing;2024-09

3. Multiscale PatchTCN-Mixer: A New Method for Extracting Spatial and Temporal Degradation Information in Remaining Useful Life Prognosis;IEEE Sensors Journal;2024-08-01

4. Feature structured domain adaptation for quality prediction of cross working conditions in industrial processes;Journal of Manufacturing Systems;2024-06

5. A comprehensive survey of machine remaining useful life prediction approaches based on pattern recognition: taxonomy and challenges;Measurement Science and Technology;2024-03-01