Machine Learning-based Monitoring
Machine Learning-Based Monitoring is a condition monitoring approach that employs machine learning algorithms to automatically detect, diagnose, or predict machine faults by learning patterns from operational data, distinguishing it from traditional rule-based or signal-processing-based methods through its reliance on data-driven model adaptation.
506
Publications
23.8K
Citations
1.8K
Authors
726
Institutions
Publications per year
2017–2026
442
Parents
506
1–5 of 506
1.8K
Hong Kong University of Science and Technology, Hong Kong SAR China
5 publications · 250 citations
5
h-index
4
h-index
4
h-index
Hong Kong University of Science and Technology, Hong Kong SAR China
4 publications · 178 citations
4
h-index
4
h-index
1–5 of 1.8K
726
Vellore Institute of Technology University
Vellore, India
10 h-index
17 publications
501 citations
Tsinghua University
Beijing, China
8 h-index
18 publications
850 citations
Politecnico di Milano
Milan, Italy
8 h-index
18 publications
1.6K citations

Centre National de la Recherche Scientifique
Paris, France
8 h-index
18 publications
748 citations

Hong Kong University of Science and Technology
Hong Kong, Hong Kong
6 h-index
10 publications
488 citations

Huazhong University of Science and Technology
Wuhan, China
6 h-index
13 publications
813 citations

University of Strathclyde
Glasgow, United Kingdom
5 h-index
8 publications
1K citations
Norwegian University of Science and Technology
Trondheim, Norway
5 h-index
7 publications
333 citations
1–8 of 726
13 publications · 514 citations
11
h-index
10 publications · 344 citations
11
h-index
9 publications · 357 citations
10
h-index
6 publications · 222 citations
9
h-index
6 publications · 529 citations
7
h-index
1–5