Online Fault Detection

Online Fault Detection is a fault detection approach that continuously monitors system behavior in real time to identify anomalies as they occur, distinguishing itself from offline methods by its immediate, on-the-fly analysis of operational data.

885

Publications

41.9K

Citations

2.7K

Authors

849

Institutions

Publications per year

2017–2026

341

Authors

2.7K

  1. CZ
    Chunhui Zhao

    State Key Laboratory of Industrial Control Technology

    10 publications · 516 citations

    10

    h-index

  2. AJ
    António J. Marques Cardoso

    University of Coimbra, Portugal

    9 publications · 771 citations

    9

    h-index

  3. WM
    Wentao Mao

    Henan Normal University, China

    9 publications · 498 citations

    9

    h-index

  4. SM
    S.D.J. McArthur

    University of Strathclyde, United Kingdom

    6 publications · 669 citations

    6

    h-index

  5. XL
    Xihui Liang

    University of Manitoba, Canada

    6 publications · 323 citations

    6

    h-index

1–5 of 2.7K

Venues

  1. IEEE Transactions on Industrial Electronics

    28 publications · 2.6K citations

    24

    h-index

  2. IEEE Transactions on Industry Applications

    24 publications · 1.7K citations

    22

    h-index

  3. IEEE Transactions on Industrial Informatics

    16 publications · 814 citations

    15

    h-index

  4. 15

    h-index

  5. IEEE Transactions on Power Delivery

    14 publications · 1.5K citations

    14

    h-index

1–5