Prof. Tonghai Wu, Xi’an Jiaotong University, China
Prof. Tonghai Wu has been a distinguished member of Xi’an Jiaotong University (XJTU) since 2006. He completed his postdoctoral research at the Materials Science and Engineering Postdoctoral Station (XJTU) from 2008 to 2010. During 2013-2014, he was a visiting scholar at UNSW, where he collaborated with Prof. Peng on condition monitoring and built partnerships with Doc. Ngai Ming Kwok and Prof. Weihua Li on image processing and wear particle sensor technology. In January 2017, he was appointed professor at the School of Mechanical Engineering at XJTU and became the Dean in 2024. He currently leads the Machine Condition Monitoring research group at XJTU, guided by Prof. Yaguo Lei.
Professional Profile:
Summary of Suitability for the Best Researcher Award:
- Professor Wu’s research expertise includes wear analysis, condition monitoring of mechanical systems, online monitoring technologies, and the development and application of artificial intelligence techniques for predicting performance and remaining useful life of mechanical systems. His research also integrates multiple techniques such as wear analysis, vibration, and oil monitoring for machine health monitoring.
Research Interests:
🔬 Prof. Wu specializes in wear analysis and condition monitoring of mechanical systems. His work focuses on:
- On-line monitoring technologies for lubrication films and wear debris
- In-situ inspection technologies using 3D image acquisition
- Development and application of AI techniques for performance prediction and lifespan assessment
- Integration of wear analysis, vibration, and oil monitoring for machine health
Field of Research (FoR):
- Tribology
- Dynamics, Vibration, and Vibration Control
- Artificial Intelligence and Image Processing
Research Collaboration:
Prof. Wu collaborates extensively with researchers globally, including in the United States, Austria, and Britain, on fundamental and applied tribology and machine condition monitoring projects.
Awards and Service to the Profession:
🏆 Competitive Grants: Secured nearly 20 million RMB in funding for research on wear debris and condition monitoring.
🔧 Consultancy: Developed integrated on-line monitoring systems for wind turbines and ocean dredger ships. Consulted for major companies in wind power, oil refining, mining, and civil engineering.
🔬 Professional Activities: Reviewed manuscripts for top journals and served as a peer reviewer for NSFC. Member of the Society of Tribologists and Lubrication Engineers and China Mechanical Engineering Society. Guest Editor for the International Journal of Rotating Machinery.
Research Impact:
📚 Prof. Wu has published over 90 high-quality papers, with over 50% in top journals, and garnered more than 2,000 citations over the past decade.
Publication top Notes:
An integrated knowledge and data model for adaptive diagnosis of lubricant conditions
Ultrasonic reflection measured oil film thickness in the slipper bearings of an aviation fuel piston pump
Spatial-temporal modeling of oil condition monitoring: A review
Fully unsupervised wear anomaly assessment of aero-bearings enhanced by multi-representation learning of deep features
Optimized Mask-RCNN model for particle chain segmentation based on improved online ferrograph sensor
Comparison-embedded evidence-CNN model for fuzzy assessment of wear severity using multi-dimensional surface images