Bayesian Prognostics
Bayesian Prognostics is a probabilistic framework for predictive maintenance that employs Bayesian inference to update the degradation state and predict the remaining useful life of a system by sequentially incorporating observed condition monitoring data.
218
Publications
13.9K
Citations
583
Authors
263
Institutions
Publications per year
2017–2026
95
Parents
218
Residual-life distributions from component degradation signals: A Bayesian approach
Nagi Gebraeel, Mark Lawley, Rong Li et al. · IIE Transactions · 2005 · 781 citations · Full text
Engineering, Industrial Engineering, Systems Engineering +17
Overview on Bayesian networks applications for dependability, risk analysis and maintenance areas
Philippe Weber, Gabriela Medina-Oliva, Christophe Simon et al. · Engineering Applications of Artificial Intelligence · 2010 · 765 citations · Full text
Engineering, Industrial Engineering, Systems Engineering +16
Dynamic Bayesian Network for Aircraft Wing Health Monitoring Digital Twin
Chenzhao Li, Sankaran Mahadevan, You Ling et al. · AIAA Journal · 2017 · 379 citations
1–5 of 218
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263

Ames Research Center
Mountain View, United States
13 h-index
32 publications
3.3K citations
Georgia Institute of Technology
Atlanta, United States
11 h-index
19 publications
1.7K citations

Beihang University
Beijing, China
9 h-index
26 publications
1.1K citations
University of Chile
Santiago, Chile
7 h-index
8 publications
440 citations
Politecnico di Milano
Milan, Italy
7 h-index
18 publications
632 citations
Xi'an High Tech University
Xi'an, China
7 h-index
27 publications
751 citations

Vanderbilt University
Nashville, United States
6 h-index
10 publications
1K citations
University of Maryland, College Park
College Park, United States
6 h-index
10 publications
350 citations
1–8 of 263
22 publications · 1.6K citations
21
h-index
19 publications · 830 citations
16
h-index
9 publications · 248 citations
9
h-index
MSSP · 7 publications · 721 citations
7
h-index
IJPHM · 6 publications · 192 citations
6
h-index
1–5