World's Best Scientists 2026 revealed!

D-Index & Metrics

Mechanical and Aerospace Engineering

D-Index
52
Citations
8697
World Ranking
1073
National Ranking
45

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

If you think any of the details on this page are incorrect, let us know.

Report an issue

We appreciate your kind effort to assist us to improve this page, it would be helpful providing us with as much detail as possible in the text box below:

Related Online Degrees & Career Pathways

For students interested in expanding their expertise beyond Mechanical and Aerospace Engineering, related fields such as speech pathology offer unique career opportunities. Understanding the options available can help engineering graduates consider alternative or complementary paths.

One key consideration is identifying programs that fit different needs, such as accessible entry requirements. Resources like easiest speech pathology programs to get into provide valuable insights for prospective students seeking manageable admission processes.

Cost remains a significant factor in choosing an online degree. Detailed information about program expenses can be found by exploring online speech pathology degree tuition, helping students budget effectively and compare financial commitments.

Veterans looking to transition into this field benefit from tailored educational pathways. Specialized options are outlined at speech pathology programs online for veterans, focusing on flexibility and military benefits.

For those eager to fast-track their studies, accelerated learning formats can be ideal. Exploring 5-year accelerated speech pathology programs offers insight into condensed timelines that allow for quicker entry into the workforce.

Best Scientists Citing Zhongxiao Peng

Trending Scientists

Recently Published Articles