Signal Processing For Diagnostics

Signal Processing for Diagnostics is a computational methodology that belongs to the class of diagnostic techniques and is specifically distinguished by its use of mathematical and algorithmic transformations of sensor-derived signals to extract fault indicators, enable feature identification, and support decision-making in the assessment of engine, hybrid vehicle, and powertrain system health.

531

Publications

21.9K

Citations

1.6K

Authors

487

Institutions

Publications per year

2017–2026

280

Authors

1.6K

  1. YL
    Yong Lv

    Wuhan University of Science and Technology, China

    7 publications · 235 citations

    7

    h-index

  2. XC
    Xuefeng Chen

    Xi'an Jiaotong University, China

    6 publications · 444 citations

    6

    h-index

  3. JL
    Jing Lin

    Xi'an Jiaotong University, China

    5 publications · 372 citations

    5

    h-index

  4. WD
    Wenhua Du

    North University of China, China

    5 publications · 194 citations

    5

    h-index

  5. JW
    Junyuan Wang

    North University of China, China

    5 publications · 194 citations

    5

    h-index

1–5 of 1.6K

Venues

  1. Mechanical Systems and Signal Processing

    MSSP · 23 publications · 1.9K citations

    22

    h-index

  2. Measurement Science and Technology

    24 publications · 1.1K citations

    20

    h-index

  3. IEEE Access

    24 publications · 795 citations

    18

    h-index

  4. Measurement

    16 publications · 951 citations

    17

    h-index

  5. Sensors

    15 publications · 556 citations

    15

    h-index

1–5