World's Best Scientists 2026 revealed!

D-Index & Metrics

Mechanical and Aerospace Engineering

D-Index
52
Citations
8697
World Ranking
1074
National Ranking
45

Zhongxiao Peng 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 Zhongxiao Peng 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: 209 publications — 47th percentile

47% of scientists in this discipline score the same or lower.

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

Zhongxiao Peng 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 Zhongxiao Peng 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: 52 D-Index — 70th percentile

70% of scientists in this discipline score the same or lower.

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

Overview

Zhongxiao Peng is affiliated with the University of New South Wales in Australia. Their research primarily focuses on engineering, with a particular emphasis on mechanical engineering and its related subfields including control and systems engineering, mechanics of materials, civil and structural engineering, and automotive engineering.

The scientist has published extensively across multiple topics, showing a strong involvement in areas such as gear and bearing dynamics analysis, machine fault diagnosis techniques, advanced machining processes and optimization, structural health monitoring techniques, tribology and lubrication engineering, lubricants and their additives, as well as additive manufacturing and 3D printing technologies.

Zhongxiao Peng's frequent publication venues include:

  • Mechanical Systems and Signal Processing
  • Tribology International
  • Wear
  • Friction
  • Applied Acoustics

Collaborations form an integral part of their scientific work, with notable frequent coauthors being Pietro Borghesani, Wade A. Smith, Robert B. Randall, Tonghai Wu, and Pan Dou. These partnerships have contributed to a significant number of publications and research development.

Some recent papers authored by Zhongxiao Peng include:

  • Machine-learning assisted laser powder bed fusion process optimization for AlSi10Mg: New microstructure description indices and fracture mechanisms (2020, Acta Materialia)
  • Planetary gearbox fault diagnosis using bidirectional-convolutional LSTM networks (2021, Mechanical Systems and Signal Processing)
  • Vibration-based anomaly detection using LSTM/SVM approaches (2021, Mechanical Systems and Signal Processing)
  • A review on polymer-based materials for underwater sound absorption (2021, Polymer Testing)
  • Use of cyclostationary properties of vibration signals to identify gear wear mechanisms and track wear evolution (2020, Mechanical Systems and Signal Processing)

Best Publications

  • Machine-learning assisted laser powder bed fusion process optimization for AlSi10Mg: New microstructure description indices and fracture mechanisms

    Qian Liu;Hongkun Wu;Moses J. Paul;Peidong He

  • Planetary gearbox fault diagnosis using bidirectional-convolutional LSTM networks

    Junchuan Shi;Dikang Peng;Zhongxiao Peng;Ziyang Zhang

  • Vibration-based anomaly detection using LSTM/SVM approaches

    Unknown

  • An integrated approach to fault diagnosis of machinery using wear debris and vibration analysis

    Z. Peng;N. Kessissoglou

  • A study of the effect of contaminant particles in lubricants using wear debris and vibration condition monitoring techniques

    Z. Peng;N.J. Kessissoglou;M. Cox

  • The use of the fractal description to characterize engineering surfaces and wear particles

    C.Q Yuan;J Li;X.P Yan;Z Peng

  • Blind vibration component separation and nonlinear feature extraction applied to the nonstationary vibration signals for the gearbox multi-fault diagnosis

    Zhixiong Li;Xinping Yan;Zhe Tian;Chengqing Yuan

  • Virtual prototype and experimental research on gear multi-fault diagnosis using wavelet-autoregressive model and principal component analysis method

    Zhixiong Li;Xinping Yan;Chengqing Yuan;Zhongxiao Peng

  • Expert system development for vibration analysis in machine condition monitoring

    Stephan Ebersbach;Zhongxiao Peng

  • The investigation of the condition and faults of a spur gearbox using vibration and wear debris analysis techniques

    S. Ebersbach;Z. Peng;N.J. Kessissoglou

  • Multi-dimensional variational mode decomposition for bearing-crack detection in wind turbines with large driving-speed variations

    Zhixiong Li;Zhixiong Li;Yu Jiang;Yu Jiang;Qiang Guo;Chao Hu

  • Wear Performance of UHMWPE and Reinforced UHMWPE Composites in Arthroplasty Applications: A Review

    Juan C. Baena;Jingping Wu;Zhongxiao Peng

  • Recent progress on decoupling diagnosis of hybrid failures in gear transmission systems using vibration sensor signal: A review

    Zhixiong Li;Zhixiong Li;Zhixiong Li;Yu Jiang;Yu Jiang;Chao Hu;Z. Peng

  • Vibration-based updating of wear prediction for spur gears

    Ke Feng;Pietro Borghesani;Wade A. Smith;Robert B. Randall

  • Optimal demodulation-band selection for envelope-based diagnostics: A comparative study of traditional and novel tools

    Wade A. Smith;Pietro Borghesani;Qing Ni;Kesheng Wang

  • An RFID-based remote monitoring system for enterprise internal production management.

    Shouqin Zhou;Weiqing Ling;Zhongxiao Peng

  • A review on polymer-based materials for underwater sound absorption

    Yifeng Fu;Imrana I. Kabir;Guan Heng Yeoh;Guan Heng Yeoh;Zhongxiao Peng

  • Development of a gear vibration indicator and its application in gear wear monitoring

    Chongqing Hu;Wade A. Smith;Robert B. Randall;Zhongxiao Peng

  • Progress and trend of sensor technology for on-line oil monitoring

    TongHai Wu;TongHai Wu;HongKun Wu;Ying Du;ZhongXiao Peng

  • Use of cyclostationary properties of vibration signals to identify gear wear mechanisms and track wear evolution

    Ke Feng;Wade A. Smith;Pietro Borghesani;Robert B. Randall

  • Wear particle classification in a fuzzy grey system

    Z. Peng;T.B. Kirk

  • Optimised Spectral Kurtosis for bearing diagnostics under electromagnetic interference

    Wade A. Smith;Zhiqi Fan;Zhongxiao Peng;Huaizhong Li

  • Tribological properties of aged nitrile butadiene rubber under dry sliding conditions

    C.L. Dong;C.Q. Yuan;X.Q. Bai;X.P. Yan

Frequent Co-Authors

Xinping Yan
Xinping Yan Wuhan University of Technology
Wade A. Smith
Wade A. Smith University of New South Wales
Robert B. Randall
Robert B. Randall University of New South Wales
Ngaiming Kwok
Ngaiming Kwok University of New South Wales
Nicole Kessissoglou
Nicole Kessissoglou University of New South Wales
Prasad Yarlagadda
Prasad Yarlagadda Queensland University of Technology
Chao Hu
Chao Hu Iowa State University
Guan Heng Yeoh
Guan Heng Yeoh University of New South Wales
Karol Miller
Karol Miller University of Western Australia
Yin Xiao
Yin Xiao Griffith University

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