Cargando…
Data-driven remaining useful life prediction based on domain adaptation
As an important part of prognostics and health management, remaining useful life (RUL) prediction can provide users and managers with system life information and improve the reliability of maintenance systems. Data-driven methods are powerful tools for RUL prediction because of their great modeling...
Autores principales: | Wen, Bin cheng, Xiao, Ming qing, Wang, Xue qi, Zhao, Xin, Li, Jian feng, Chen, Xin |
---|---|
Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
PeerJ Inc.
2021
|
Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8444085/ https://www.ncbi.nlm.nih.gov/pubmed/34604520 http://dx.doi.org/10.7717/peerj-cs.690 |
Ejemplares similares
-
Deep learning-based anomaly-onset aware remaining useful life estimation of bearings
por: Kamat, Pooja Vinayak, et al.
Publicado: (2021) -
An enhanced CNN-LSTM remaining useful life prediction model for aircraft engine with attention mechanism
por: Li, Hao, et al.
Publicado: (2022) -
An adaptive dimension differential evolution algorithm based on ranking scheme for global optimization
por: Sung, Tien-Wen, et al.
Publicado: (2022) -
A hybrid anomaly detection method for high dimensional data
por: Zhang, Xin, et al.
Publicado: (2023) -
A 2D image 3D reconstruction function adaptive denoising algorithm
por: Wang, Feng, et al.
Publicado: (2023)