Research Interests:

Condition Monitoring and Fault Diagnosis of Machinery

Signal Processing

Electro-mechanical System Dynamics

Artificial Intelligence

Academic Qualification:

September 1993 – July 1997, BSc, Automotive Engineering, Jilin University (Original Jilin University of Technology), Changchun, P. R. China

September 1997 – March 2000, MSc, Mechanical Design and Theory, Kunming University of Science and Technology, Kunming, P. R. China

March 2000 – July 2003, PhD, Power Machinery and Engineering, Dalian University of Technology, Dalian, P. R. China

Occupational Career

October 2003 – August 2005, Postdoctoral Research Fellow, Department of Precision Instruments and Mechanology, Tsinghua University

May 2006 – May 2007, Postdoctoral Research Fellow, Department of Mechanical Engineering, University of Alberta, Canada

December 2010 –August 2011, Visiting Professor, Department of Mechanical Engineering, University of Ottawa, Canada

November 2015 – November 2016, Visiting Professor, Department of Mechanical Engineering, University of Alberta, Canada

August 2005 – Present, Lecturer (2005), Associate Professor (2008), Professor (2012), University of Science and Technology Beijing

Funded Projects:

Dr. Feng has served as the PI of 1 National Key Research and Development Project (2018YFC0810500) and 5 projects funded by National Natural Science Foundation of China (50705007, 51075028, 11272047, 51475038, 51875034).

Selected Publications

[1]Zhipeng Feng, Xiaowang Chen, Ming J. Zuo, Induction motor stator current AM-FM model and demodulation analysis for planetary gearbox fault diagnosis, IEEE Transactions on Industrial Informatics, 2019, 15(4): 2386-2394

[2]Zhipeng Feng, Xiaowang Chen, Tianyang Wang, Time-varying demodulation analysis for rolling bearing fault diagnosis under variable speed conditions, Journal of Sound and Vibration, 2017, 400: 71-85

[3]Zhipeng Feng, Haoqun Ma, Ming J. Zuo, Vibration signal models for fault diagnosis of planet bearings, Journal of Sound and Vibration, 2016, 370: 372-393

[4] Zhipeng Feng, Ming Liang, Complex signal analysis for wind turbine planetary gearbox fault diagnosis via iterative atomic decomposition thresholding, Journal of Sound and Vibration, 2014, 333: 5196-5211

[5]Zhipeng Feng, Ming J. Zuo, Vibration signal models for fault diagnosis of planetary gearboxes, Journal of Sound and Vibration, 2012, 331: 4919-4939 (ESI Highly Cited Paper)

[6]Zhipeng Feng, Fulei Chu, Ming J. Zuo, Time-frequency analysis of time-varying modulated signals based on improved energy separation by iterative generalized demodulation, Journal of Sound and Vibration, 2011, 330: 1225-1243

[7]Zhipeng Feng, Fulei Chu, Application of atomic decomposition to gear damage detection, Journal of Sound and Vibration, 2007, 302: 138-151

[8]Zhipeng Feng, Xinnan Yu, Dong Zhang, Ming Liang, Generalized adaptive mode decomposition for nonstationary signal analysis of rotating machinery: Principle and applications, Mechanical Systems and Signal Processing, 2020, 136: 106530

[9]Zhipeng Feng, Xiaowang Chen, Adaptive iterative generalized demodulation for nonstationary complex signal analysis: Principle and application in rotating machinery fault diagnosis, Mechanical Systems and Signal Processing, 2018, 110: 1-27

[10]Zhipeng Feng, Xiaowang Chen, Ming Liang, Joint envelope and frequency order spectrum analysis based on iterative generalized demodulation for planetary gearbox fault diagnosis under nonstationary conditions, Mechanical Systems and Signal Processing, 2016, 76-77: 242-264

[11]Zhipeng Feng, Xiaowang Chen, Ming Liang, Fei Ma, Time-frequency demodulation analysis based on iterative generalized demodulation for fault diagnosis of planetary gearbox under nonstationary conditions, Mechanical Systems and Signal Processing, 2015, 62-63: 54-74

[12]Zhipeng Feng, Xiaowang Chen, Ming Liang, Iterative generalized synchrosqueezing transform for fault diagnosis of wind turbine planetary gearbox under nonstationary conditions, Mechanical Systems and Signal Processing, 2015, 52-53: 360-375 (ESI Highly Cited Paper)

[13]Zhipeng Feng, Ming Liang, Fulei Chu, Recent advances in time-frequency analysis methods for machinery fault diagnosis: A review with application examples, Mechanical Systems and Signal Processing, 2013, 38: 165-205 (ESI Highly Cited Paper)

[14]Zhipeng Feng, Ming Liang, Yi Zhang, Shumin Hou, Fault diagnosis for wind turbine planetary gearboxes via demodulation analysis based on ensemble empirical mode decomposition and energy separation, Renewable Energy, 2012, 47: 112-126 (ESI Highly Cited Paper)

[15]Zhipeng Feng, Yakai Zhou, Ming J. Zuo, Fulei Chu, Xiaowang Chen, Atomic decomposition and sparse representation for complex signal analysis in machinery fault diagnosis: A review with examples, Measurement, 2017, 103: 106-132

[16]Zhipeng Feng, Ming J. Zuo, Rujiang Hao, Fulei Chu, Mohamed El Badaoui, Gear damage assessment based on cyclic spectral analysis, IEEE Transactions on Reliability, 2011, 60(1): 21-32

[17]Chuan Zhao, Zhipeng Feng*, Xiukun Wei, Yong Qin, Sparse classification based on dictionary learning for planet bearing fault identification, Expert Systems with Applications, 2018, 108: 233-245

[18]Fulei Chu, Zhike Peng, Zhipeng Feng, Zhinong Li, Modern Signal Processing Methods in Machinery Fault Diagnosis, Beijing: Science Press, 2009 (in Chinese)

[19]Zhipeng Feng, Fulei Chu, Ming J. Zuo, Planetary Gearbox Fault Diagnosis Methods, Beijing: Science Press, 2015 (in Chinese)

[20] Zhipeng Feng, Fulei Chu, Ming J. Zuo, Complex Nonstationary Signal Analysis Methods: Principles and Applications in Mechanical System Fault Diagnosis, Beijing: Science Press, 2018 (in Chinese)