Ph.D., Mechanical Engineering, Southampton University, 1993.8

M.S., Engineering Mechanics, Tianjin University, 1985.1

B.S., Mechanical Engineering, Jiangxi Institute of Metallurgy, 1982.1

Department of Mechanical Engineering, Tsinghua University, Faculty, 2013.1-Present

Department of Precision Instruments & Mechanology, Tsinghua University, Faculty, 1994.9-2012.12

Department of Mechanical Engineering, Southampton University, Research Associate, 1993.9-1994.8

Department of Mechanics, Tianjin University, Lecturer, 1985.1-1989.8

Vibration Theory: for graduate students, every fall semester

English Scientific Paper Writing in Mechanical Engineering: for graduate students, every fall semester

Rotor Dynamics: for graduate students, every spring semester

Areas of Research Interests/Research Projects:

Mainly engaged in the research of dynamics and vibration, machine fault diagnostics and vibration control, presided over and participated in more than 30 research projects, including the National Outstanding Youth Science Foundation, National Science and Technology Major Project, National Defense 973 Project, National Natural Science Foundation Key Project, 863 Program Projects, etc. The research work currently being carried out includes: 1. Machine fault diagnosis: fault diagnosis of key components such as bearings and gears, monitoring and diagnosis of wind turbine blades, monitoring and diagnosis of elevators and escalators, fault diagnosis of rotating shaft cracks, bearing remaining life prediction, and application of deep learning in fault diagnosis. 2. Rotating machinery dynamics: gas-solid coupling dynamics analysis of aero-engine rotors, temperature gradients effects and electromagnetic effects on rotor dynamics. 3. Vibration control: The damping characteristics of composite materials and their role in vibration suppression, the application of acoustic black hole theory in vibration control, and the equivalence study of laser shock and explosion shock.

1. "Some dynamics theory and application of complex nonlinear system" won the second level award of the 2003 National Natural Science Award, ranking third;

2. "Some Theories and Methods of Mechanical Equipment Health Maintenance" won the first level award of the Ministry of Education Natural Science Award in 2011, ranking first;

3. "Development and Research of 300MW Turbogenerator Vibration Monitoring, Analysis and Diagnosis System" won the second level award of Guangdong Province Science and Technology Progress Award in 2003, ranking first;

4. "Research and Application of Hydropower Unit Condition Monitoring and Fault Diagnosis Technology" won the second level award of Science and Technology Progress Award of the Ministry of Education in 2006, ranking first;

5. "Dynamics theory and method of complex nonlinear system" won the first level award of Tianjin Natural Science Award in 2002, ranking fifth;

6. "New methods of rotor system fault diagnosis and its application research" won the second level award of Jiangxi Province Natural Science Award in 2014, ranking third;

7. "Guangzhou Storage Power Plant Unit Stability State Monitoring and Tracking Analysis System PSTA-I" won the second level award of Guangdong Province Science and Technology Progress Award in 1999, ranking third;

8. "Rotor Machinery Intelligent Monitoring and Diagnosis Technology" won the second level award of the 2009 China Instrumentation Society Science and Technology Award, ranking second;

9. "Development and Research on the Status Monitoring, Analysis and Diagnosis System of Hydropower Units" won the third level award of the 2003 China Electric Power Science and Technology Award, ranking first;

10. Selected as the "Cross-Century Excellent Talent Training Program" by the Ministry of Education in 2003;

11. Won the 2004 National Outstanding Young Researcher Award from Natural Science Foundation of China;

12. In 2006, received the special government allowance from the State Council.

13. Selected as a Highly Cited Scholar by Elsevier in the field of Mechanical Engineering for six consecutive years from 2014 to 2019.

Professor Fulei Chu received his PhD from Southampton University in UK. He is the Vice President of the Chinese Society for Vibration Engineering (CSVE) and Chairman of the Technical Committee for Machine Fault Diagnostics of CSVE. He serves as members of the editorial board for many journals, including Journal of Sound and Vibration, Journal of Mechanical Engineering Science, Journal of Vibration Engineering, Frontiers of Mechanical Engineering, Journal of Vibration and Shock and others. His research interests include rotating machinery dynamics, machine condition monitoring and fault detection, nonlinear vibration and vibration control. He has published more than 300 papers in peer review journals, including 36 papers in the Journal of Sound and Vibration and 31 papers in the journal of Mechanical Systems and Signal Processing. He has also authored 3 books and edited 2 conference proceedings. He has received many awards in China, including the Outstanding Young Researcher Award from Natural Science Foundation of China. Main research achievements include: 1. The nonlinear dynamics mechanism of typical faults of rotating machinery is found. The typical characteristics of the rotor rubbing fault were obtained through experiments, and the effectiveness of the rubbing fault model was verified; the local stiffness hardening phenomenon of the rotor system caused by the rubbing fault was found, and a rubbing position diagnosis method based on the local dynamic stiffness identification was proposed; A piecewise linear stiffness and damping foundation looseness failure model is described, and the dynamic behavior of this kind of faulty rotor is accurately described, and experimental verification is carried out. The model is widely used at home and abroad. 2. An adaptive decomposition theory under multi-source interference is proposed. If the intrinsic similarity and the approximate narrow-band conditions are not satisfied, the classical adaptive decomposition will produce pseudo components. The inherent law of adaptive decomposition of multi-source signals is revealed, and a quantitative criterion for the adaptive decomposition is proposed to automatically extract the real Intrinsic Mode Function (IMF) with a single frequency. 3. An accurate identification method for multi-source modulation components is proposed. The multi-source modulation mechanism of typical mechanical system signals is revealed. An iterative generalized demodulation quasi-stationary separation strategy is proposed. It breaks through the limitation of the time-frequency resolution by optimizing the basis function, solves the problem of low time-frequency resolution and serious interference, and helps accurately identify the intricate overlapping time-varying frequency components. 4. A model for the optimal selection of multi-source fault features is established. An autonomous joint optimization model for selecting fault features and for determining the key parameters of the SVM is proposed, and A “one to others” classification strategy and multi-classification support vector machine (SVM) are defined. The problems associated with the optimal fault feature selection and multi-category classification when using nonuniformly distributed, small fault samples are solved without any classification blind zone, thus significantly improving the generalization ability, classification accuracy, and computational efficiency of the SVM. The proposed “one to others” SVM has become a general SVM algorithm.