World's Best Scientists 2026 revealed!

D-Index & Metrics

Engineering and Technology

D-Index
46
Citations
7197
World Ranking
5233
National Ranking
1019

Overview

Zhipeng Feng is affiliated with the University of Science and Technology Beijing in China and focuses on engineering research, particularly in mechanical engineering and related subfields. Their work spans multiple aspects of machine diagnostics, fault detection, and reliability analysis within mechanical systems.

The scientist has contributed extensively to the field of Mechanical Engineering with a substantial number of publications. Their research interests primarily include:

  • Machine Fault Diagnosis Techniques
  • Gear and Bearing Dynamics Analysis
  • Engineering Diagnostics and Reliability
  • Structural Health Monitoring Techniques
  • Fault Detection and Control Systems
  • Tribology and Lubrication Engineering
  • Advanced Machining Processes and Optimization

Zhipeng Feng's recent published papers detail investigations into fault diagnosis methods for planetary gearboxes and rotating machinery under varying operational conditions. Some notable works include:

  • "Planetary gearbox fault diagnosis via rotary encoder signal analysis," 2020, Mechanical Systems and Signal Processing
  • "Induction motor stator current analysis for planetary gearbox fault diagnosis under time-varying speed conditions," 2020, Mechanical Systems and Signal Processing
  • "Component matching chirplet transform via frequency-dependent chirp rate for wind turbine planetary gearbox fault diagnostics under variable speed condition," 2021, Mechanical Systems and Signal Processing
  • "Enhancement of time-frequency post-processing readability for nonstationary signal analysis of rotating machinery: Principle and validation," 2021, Mechanical Systems and Signal Processing
  • "Discriminative dictionary learning based sparse representation classification for intelligent fault identification of planet bearings in wind turbine," 2020, Renewable Energy

The majority of Feng's contributions have been published in the journal Mechanical Systems and Signal Processing, where they have authored 16 papers. Other frequent publication venues include:

  • IEEE Transactions on Instrumentation and Measurement
  • IEEE Transactions on Power Electronics
  • IEEE Sensors Journal
  • Applied Sciences

They maintain collaboration with several researchers in their field, with frequent coauthors including Xiaowang Chen, Tianyang Wang, Fulei Chu, Dong Zhang, and Rongzhou Lin, each contributing to improving fault diagnosis technologies and related engineering disciplines.

The research mainly falls under the broader field of Engineering, contributing to the advancement of diagnostics and control in mechanical systems through detailed analysis techniques and innovative signal processing methods. These efforts contribute to addressing challenges in industrial machinery maintenance and reliability monitoring.

Best Publications

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

    Zhipeng Feng;Ming Liang;Fulei Chu

  • Vibration signal models for fault diagnosis of planetary gearboxes

    Zhipeng Feng;Ming J. Zuo

  • Vibration based condition monitoring and fault diagnosis of wind turbine planetary gearbox: A review

    Tianyang Wang;Qinkai Han;Fulei Chu;Zhipeng Feng

  • Dynamic modeling of gearbox faults: A review

    Xihui Liang;Ming J. Zuo;Zhipeng Feng;Zhipeng Feng

  • 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

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

    Zhipeng Feng;Xiaowang Chen;Ming Liang

  • Fault diagnosis of planetary gearboxes via torsional vibration signal analysis

    Zhipeng Feng;Ming J. Zuo;Ming J. Zuo

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

    Zhipeng Feng;Ming Liang

  • Adaptive Mode Decomposition Methods and Their Applications in Signal Analysis for Machinery Fault Diagnosis: A Review With Examples

    Zhipeng Feng;Dong Zhang;Ming J. Zuo

  • Time-varying demodulation analysis for rolling bearing fault diagnosis under variable speed conditions

    Zhipeng Feng;Xiaowang Chen;Tianyang Wang

  • Atomic decomposition and sparse representation for complex signal analysis in machinery fault diagnosis: A review with examples

    Zhipeng Feng;Yakai Zhou;Ming J. Zuo;Ming J. Zuo;Fulei Chu

  • 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

  • Time-frequency representation based on robust local mean decomposition for multicomponent AM-FM signal analysis

    Zhiliang Liu;Yaqiang Jin;Ming J. Zuo;Ming J. Zuo;Zhipeng Feng

  • Joint amplitude and frequency demodulation analysis based on local mean decomposition for fault diagnosis of planetary gearboxes

    Zhipeng Feng;Ming J. Zuo;Ming J. Zuo;Jian Qu;Tao Tian

  • A load identification method based on wavelet multi-resolution analysis

    Zong Li;Zhipeng Feng;Fulei Chu

  • Time–frequency analysis of time-varying modulated signals based on improved energy separation by iterative generalized demodulation

    Zhipeng Feng;Fulei Chu;Ming J. Zuo

  • Time-Frequency demodulation analysis via Vold-Kalman filter for wind turbine planetary gearbox fault diagnosis under nonstationary speeds

    Zhipeng Feng;Wenying Zhu;Dong Zhang

  • Complex signal analysis for wind turbine planetary gearbox fault diagnosis via iterative atomic decomposition thresholding

    Zhipeng Feng;Ming Liang

  • Complex signal analysis for planetary gearbox fault diagnosis via shift invariant dictionary learning

    Zhipeng Feng;Ming Liang

  • A new SKRgram based demodulation technique for planet bearing fault detection

    Tianyang Wang;Qinkai Han;Fulei Chu;Zhipeng Feng

  • Iterative generalized time–frequency reassignment for planetary gearbox fault diagnosis under nonstationary conditions

    Xiaowang Chen;Zhipeng Feng

  • Joint amplitude and frequency demodulation analysis based on intrinsic time-scale decomposition for planetary gearbox fault diagnosis

    Zhipeng Feng;Xuefeng Lin;Ming J. Zuo;Ming J. Zuo

  • Application of atomic decomposition to gear damage detection

    Zhipeng Feng;Zhipeng Feng;Fulei Chu

Frequent Co-Authors

Ming J. Zuo
Ming J. Zuo University of Alberta
Fulei Chu
Fulei Chu Tsinghua University
Ming Liang
Ming Liang University of Ottawa
Qinkai Han
Qinkai Han Tsinghua University
Zhike Peng
Zhike Peng Shanghai Jiao Tong University
Zhaoye Qin
Zhaoye Qin Tsinghua University
Jay Lee
Jay Lee University of Maryland, College Park
Wen-Ming Zhang
Wen-Ming Zhang Shanghai Jiao Tong University
Dong Wang
Dong Wang Shanghai Jiao Tong University
Ivan W. Selesnick
Ivan W. Selesnick New York University

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