Data-driven Diagnosis

Data-Driven Diagnosis is a formal diagnostic approach within hybrid, maintenance, robot, and sensor diagnostics that relies on empirical data and statistical or machine learning models to identify, isolate, or characterize system faults or anomalies without requiring explicit analytical models of system behavior.

403

Publications

28K

Citations

1.5K

Authors

543

Institutions

Publications per year

2017–2026

321

Authors

1.5K

  1. SX
    Steven X. Ding

    University of Duisburg-Essen, Germany

    7 publications · 2K citations

    7

    h-index

  2. KR
    Krishna R. Pattipati

    University of Connecticut, United States

    6 publications · 214 citations

    6

    h-index

  3. LG
    Liang Gao

    Huazhong University of Science and Technology, China

    5 publications · 3.3K citations

    5

    h-index

  4. BG
    Bin Gou

    Southwest Jiaotong University, China

    4 publications · 266 citations

    4

    h-index

  5. XL
    Xiang Li

    Xi'an Jiaotong University, China

    4 publications · 209 citations

    4

    h-index

1–5 of 1.5K

Venues

  1. IEEE Transactions on Industrial Informatics

    18 publications · 2K citations

    18

    h-index

  2. IEEE Transactions on Industrial Electronics

    15 publications · 3.5K citations

    15

    h-index

  3. IEEE Access

    14 publications · 1.2K citations

    14

    h-index

  4. Sensors

    13 publications · 829 citations

    13

    h-index

  5. 13

    h-index

1–5