World's Best Scientists 2026 revealed!

D-Index & Metrics

Mechanical and Aerospace Engineering

D-Index
54
Citations
9974
World Ranking
968
National Ranking
40

Ming Liang publication distribution in Mechanical and Aerospace Engineering in 2026

The chart shows the distribution of publications by all Research.com ranked scientists in the field of Mechanical and Aerospace Engineering in 2026. The highlighted bar marks where Ming Liang sits on this spectrum.

47–56 publications: 10 scientists 57–66 publications: 23 scientists 67–76 publications: 32 scientists 77–86 publications: 62 scientists 87–96 publications: 67 scientists 97–106 publications: 91 scientists 107–116 publications: 113 scientists 117–126 publications: 115 scientists 127–136 publications: 130 scientists 137–146 publications: 140 scientists 147–156 publications: 155 scientists 157–166 publications: 132 scientists 167–176 publications: 133 scientists 177–186 publications: 130 scientists 187–196 publications: 140 scientists 197–206 publications: 115 scientists 207–216 publications: 125 scientists 217–226 publications: 117 scientists 227–236 publications: 99 scientists 237–246 publications: 92 scientists 247–256 publications: 100 scientists 257–266 publications: 95 scientists 267–276 publications: 88 scientists 277–286 publications: 77 scientists 287–296 publications: 74 scientists 297–306 publications: 74 scientists 307–316 publications: 62 scientists 317–326 publications: 70 scientists 327–336 publications: 59 scientists 337–346 publications: 58 scientists 347–356 publications: 45 scientists 357–366 publications: 44 scientists 367–376 publications: 36 scientists 377–386 publications: 41 scientists 387–396 publications: 32 scientists 397–406 publications: 23 scientists 407–416 publications: 28 scientists 417–426 publications: 27 scientists 427–436 publications: 25 scientists 437–446 publications: 23 scientists 447–456 publications: 23 scientists 457–466 publications: 20 scientists 467–476 publications: 12 scientists 477–486 publications: 24 scientists 487–496 publications: 18 scientists 497–506 publications: 12 scientists 507–516 publications: 13 scientists 517–526 publications: 21 scientists 527–536 publications: 12 scientists 537–546 publications: 8 scientists 547–556 publications: 16 scientists 557–566 publications: 3 scientists 567–576 publications: 11 scientists 577–586 publications: 6 scientists 587–596 publications: 5 scientists 597–606 publications: 6 scientists 607–616 publications: 7 scientists 617–626 publications: 7 scientists 627–636 publications: 10 scientists 637–646 publications: 4 scientists 647–656 publications: 3 scientists 657–658 publications: 2 scientists 659+ publications: 100 scientists
47 publications 659+

This scientist: 173 publications — 34th percentile

34% of scientists in this discipline score the same or lower.

The last bar groups every scientist with 659 publications or more.

Ming Liang D-index placement in Mechanical and Aerospace Engineering in 2026

The chart shows the D-index (discipline H-index) distribution of Mechanical and Aerospace Engineering scientists ranked by Research.com in 2026. The highlighted bar marks where Ming Liang sits on this spectrum.

30 D-Index: 83 scientists 31 D-Index: 113 scientists 32 D-Index: 144 scientists 33 D-Index: 153 scientists 34 D-Index: 189 scientists 35 D-Index: 158 scientists 36 D-Index: 139 scientists 37 D-Index: 127 scientists 38 D-Index: 130 scientists 39 D-Index: 126 scientists 40 D-Index: 104 scientists 41 D-Index: 100 scientists 42 D-Index: 107 scientists 43 D-Index: 101 scientists 44 D-Index: 103 scientists 45 D-Index: 79 scientists 46 D-Index: 88 scientists 47 D-Index: 70 scientists 48 D-Index: 83 scientists 49 D-Index: 44 scientists 50 D-Index: 64 scientists 51 D-Index: 56 scientists 52 D-Index: 50 scientists 53 D-Index: 48 scientists 54 D-Index: 58 scientists 55 D-Index: 52 scientists 56 D-Index: 48 scientists 57 D-Index: 42 scientists 58 D-Index: 34 scientists 59 D-Index: 42 scientists 60 D-Index: 37 scientists 61 D-Index: 42 scientists 62 D-Index: 44 scientists 63 D-Index: 22 scientists 64 D-Index: 33 scientists 65 D-Index: 29 scientists 66 D-Index: 23 scientists 67 D-Index: 29 scientists 68 D-Index: 24 scientists 69 D-Index: 19 scientists 70 D-Index: 34 scientists 71 D-Index: 26 scientists 72 D-Index: 19 scientists 73 D-Index: 18 scientists 74 D-Index: 19 scientists 75 D-Index: 14 scientists 76 D-Index: 19 scientists 77 D-Index: 8 scientists 78 D-Index: 18 scientists 79 D-Index: 16 scientists 80 D-Index: 12 scientists 81 D-Index: 17 scientists 82 D-Index: 11 scientists 83 D-Index: 16 scientists 84 D-Index: 7 scientists 85 D-Index: 9 scientists 86 D-Index: 8 scientists 87 D-Index: 6 scientists 88 D-Index: 6 scientists 89 D-Index: 7 scientists 90 D-Index: 10 scientists 91 D-Index: 4 scientists 92 D-Index: 4 scientists 93+ D-Index: 100 scientists
30 D-Index 93+

This scientist: 54 D-Index — 73rd percentile

73% of scientists in this discipline score the same or lower.

The last bar groups every scientist with 93 D-Index or more.

Overview

Ming Liang is affiliated with the University of Ottawa in Canada and has contributed extensively to the field of engineering, with a focus on mechanical engineering and related subfields. Their research spans across areas such as machine fault diagnosis techniques, gear and bearing dynamics analysis, and materials engineering related to magnesium and aluminum alloys.

Their documented research topics include:

  • Machine Fault Diagnosis Techniques
  • Gear and Bearing Dynamics Analysis
  • Advanced Machining Processes and Optimization
  • Magnesium Alloys: Properties and Applications
  • Aluminum Alloys Composites Properties
  • Icing and De-icing Technologies
  • Tribology and Lubrication Engineering

Ming Liang has published in multiple venues, demonstrating a range of interests primarily in applied engineering and materials science. Frequent publication venues include:

  • Journal of Research in Applied Mathematics
  • Mechanical Systems and Signal Processing
  • Journal of Sound and Vibration
  • Measurement Science and Technology
  • Materials Science and Engineering A

Their work includes research papers published over recent years, addressing topics such as fault diagnosis in mechanical systems and material behavior. Recent papers include:

  • "Permanent magnet synchronous generator stator current AM-FM model and joint signature analysis for planetary gearbox fault diagnosis," 2020, Mechanical Systems and Signal Processing
  • "Analytical vibration signal model and signature analysis in resonance region for planetary gearbox fault diagnosis," 2021, Journal of Sound and Vibration
  • "Pre-classified reservoir computing for the fault diagnosis of 3D printers," 2020, Mechanical Systems and Signal Processing
  • "Fault feature analysis and detection of progressive localized gear tooth pitting and spalling," 2022, Measurement Science and Technology
  • "Effect of Li addition on bending behavior of extruded Mg-2Zn alloy sheet," 2023, Materials Science and Engineering A

Collaborations with frequent coauthors are notable in their profile, highlighting interdisciplinary efforts. Frequent coauthors include:

  • Zhipeng Feng
  • Ying Han
  • Peng Ding
  • Chengyi Zhang
  • Aoran Gao

Ming Liang's subfields of study further clarify the areas of expertise and research focus, including:

  • Mechanical Engineering
  • Control and Systems Engineering
  • Mechanics of Materials
  • Biomedical Engineering
  • Civil and Structural Engineering

Best Publications

  • Recent advances in time–frequency analysis methods for machinery fault diagnosis: A review with application examples

    Zhipeng Feng;Ming Liang;Fulei Chu

  • Spectral kurtosis for fault detection, diagnosis and prognostics of rotating machines: A review with applications

    Yanxue Wang;Yanxue Wang;Jiawei Xiang;Richard Markert;Ming Liang

  • Fault diagnosis for wind turbine planetary gearboxes via demodulation analysis based on ensemble empirical mode decomposition and energy separation

    Zhipeng Feng;Ming Liang;Yi Zhang;Shumin Hou

  • Time-frequency signal analysis for gearbox fault diagnosis using a generalized synchrosqueezing transform

    Chuan Li;Chuan Li;Ming Liang

  • A smoothness index-guided approach to wavelet parameter selection in signal de-noising and fault detection

    I. Soltani Bozchalooi;Ming Liang

  • Rolling element bearing fault diagnosis via fault characteristic order (FCO) analysis

    Tianyang Wang;Tianyang Wang;Ming Liang;Jianyong Li;Weidong Cheng

  • An adaptive SK technique and its application for fault detection of rolling element bearings

    Yanxue Wang;Ming Liang

  • Iterative generalized synchrosqueezing transform for fault diagnosis of wind turbine planetary gearbox under nonstationary conditions

    Zhipeng Feng;Xiaowang Chen;Ming Liang

  • An energy operator approach to joint application of amplitude and frequency-demodulations for bearing fault detection ☆

    Ming Liang;I. Soltani Bozchalooi

  • Fault severity assessment for rolling element bearings using the Lempel–Ziv complexity and continuous wavelet transform

    Hoonbin Hong;Ming Liang

  • Detection and diagnosis of bearing and cutting tool faults using hidden Markov models

    Tony Boutros;Ming Liang

  • Fault diagnosis of wind turbine planetary gearbox under nonstationary conditions via adaptive optimal kernel time–frequency analysis

    Zhipeng Feng;Ming Liang

  • Wavelet-Based Detection of Beam Cracks Using Modal Shape and Frequency Measurements

    Jiawei Xiang;Ming Liang

  • A joint resonance frequency estimation and in-band noise reduction method for enhancing the detectability of bearing fault signals

    I. Soltani Bozchalooi;Ming Liang

  • Criterion fusion for spectral segmentation and its application to optimal demodulation of bearing vibration signals

    Chuan Li;Chuan Li;Ming Liang;Tianyang Wang

  • Bearing fault diagnosis under unknown time-varying rotational speed conditions via multiple time-frequency curve extraction

    Huan Huang;Natalie Baddour;Ming Liang

  • Time–frequency analysis based on Vold-Kalman filter and higher order energy separation for fault diagnosis of wind turbine planetary gearbox under nonstationary conditions

    Zhipeng Feng;Sifeng Qin;Ming Liang

  • Generalized stepwise demodulation transform and synchrosqueezing for time–frequency analysis and bearing fault diagnosis

    Juanjuan Shi;Ming Liang;Dan-Sorin Necsulescu;Yunpeng Guan

  • Identification of multiple transient faults based on the adaptive spectral kurtosis method

    Yanxue Wang;Ming Liang

  • Damage detection method for wind turbine blades based on dynamics analysis and mode shape difference curvature information

    Yanfeng Wang;Ming Liang;Jiawei Xiang

  • Chatter detection based on probability distribution of wavelet modulus maxima

    Lei Wang;Ming Liang

Frequent Co-Authors

Chuan Li
Chuan Li Chongqing Technology and Business University
Zhipeng Feng
Zhipeng Feng University of Science and Technology Beijing
Dejie Yu
Dejie Yu Hunan University
Jie Liu
Jie Liu Hunan University
Zhike Peng
Zhike Peng Shanghai Jiao Tong University
Wen-Ming Zhang
Wen-Ming Zhang Shanghai Jiao Tong University
Fulei Chu
Fulei Chu Tsinghua University
Xiaoli Li
Xiaoli Li Singapore University of Technology and Design
Ming J. Zuo
Ming J. Zuo University of Alberta
Qingbo He
Qingbo He Shanghai Jiao Tong University

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