Data-driven Condition Assessment

Data-Driven Condition Assessment is a data-centric methodology within asset condition assessment that leverages empirical data, statistical analysis, and computational models to objectively evaluate the health and performance state of physical assets without reliance on purely heuristic or rule-based judgments.

41

Publications

1.4K

Citations

151

Authors

80

Institutions

Publications per year

2017–2026

27

Authors

151

  1. SS
    Siamak Saliminejad

    Texas A&M University, United States

    2 publications · 49 citations

    2

    h-index

  2. NG
    Nasir G. Gharaibeh

    Texas A&M University, United States

    2 publications · 49 citations

    2

    h-index

  3. XJ
    Xingxing Jiang

    Soochow University, China

    1 publications · 22 citations

    1

    h-index

  4. ZY
    Zhao Yang Dong

    The University of Sydney, Australia

    1 publications · 57 citations

    1

    h-index

  5. JL
    Jizhen Liu

    North China Electric Power University, China

    1 publications · 30 citations

    1

    h-index

1–5 of 151

Venues

  1. 3

    h-index

  2. IEEE Transactions on Industrial Electronics

    2 publications · 163 citations

    2

    h-index

  3. IEEE Transactions on Industrial Informatics

    2 publications · 92 citations

    2

    h-index

  4. Journal of Computing in Civil Engineering

    2 publications · 94 citations

    2

    h-index

  5. IEEE Access

    2 publications · 66 citations

    2

    h-index

1–5