Senior Engineer, China Railway Engineering Corporation, China
Dr. Yuanke Wu is a postdoctoral fellow at China Railway Engineering Equipment Group Co., Ltd., with a doctorate from Southwest Jiaotong University. He specializes in the study of tunnel boring machine (TBM) main bearings and surface science. Dr. Wu has led pioneering research through a self-developed full-scale TBM main bearing test bench, combining operational and life-cycle simulations with novel evaluation methodologies. His entropy weight–grey correlation degree method has set a benchmark in bearing performance diagnostics. With several patents and six peer-reviewed journal articles, he bridges theoretical insight and industrial application. As a Young Editorial Board Member of the Journal of Dynamics, Monitoring and Diagnostics, Dr. Wu plays an active role in academic discourse. His work significantly contributes to improving the reliability and lifespan evaluation of critical mechanical systems used in large-scale infrastructure projects.
Professional Profile
Education
Dr. Yuanke Wu earned his Ph.D. from Southwest Jiaotong University, a renowned Chinese institution known for excellence in railway and transportation engineering. His academic background emphasizes mechanical engineering, tribology, and systems dynamics, with a strong research focus on TBM components and bearing systems. Throughout his doctoral journey, Dr. Wu developed expertise in experimental mechanics, condition monitoring, and the digital twin modeling of large-scale machinery. His work on surface science and contact mechanics laid the foundation for his subsequent innovations in TBM main bearing diagnostics. Dr. Wu’s rigorous academic training has enabled him to seamlessly integrate advanced theoretical modeling with practical industrial applications, an approach that defines his current postdoctoral research at China Railway Engineering Equipment Group.
Experience
Dr. Wu currently serves as a postdoctoral researcher at China Railway Engineering Equipment Group Co., Ltd., where he focuses on the digital diagnostics and lifespan evaluation of TBM main bearings. He has successfully built and operated a full-scale main bearing test bench capable of replicating real-world load spectrums for operational and life-cycle assessments. His practical work extends to software development for digital condition monitoring systems and the application of advanced algorithms for wear prediction and fault diagnostics. In addition to his experimental contributions, Dr. Wu has co-authored multiple high-impact papers, participated in national-level research projects like the Henan Province Science and Technology Research Project (Grant No. 242102221010), and applied for seven Chinese patents. He brings together engineering design, system testing, and data analytics in a highly specialized field, making him an asset to both academic and industrial environments.
Research Focus
Dr. Wu’s research primarily revolves around main bearings of tunnel boring machines (TBMs)—crucial components for large-scale infrastructure machinery. His work involves tribological analysis, surface science, and the development of diagnostic tools for bearing wear and fault detection. A key innovation is his entropy weight–grey correlation degree method, which provides a quantitative approach to assess bearing performance under realistic load conditions. He has constructed a digital life analysis platform integrated with a full-scale test bench, enabling dynamic simulations of operational conditions. His interests also extend to the tribological behavior of high-speed railway brakes, indicating a broader focus on mechanical interface reliability. By combining experimental techniques with data-driven modeling, Dr. Wu’s research contributes significantly to the predictive maintenance and lifecycle management of mission-critical components in transportation and tunneling systems.
Publication Top Notes
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A method for evaluating the performance of main bearings of TBM based on entropy weight–grey correlation degree
Sensors, 2021, 25(15), 4715. [DOI: https://doi.org/10.3390/s25154715]
Summary: Proposes a novel evaluation framework using entropy weighting and grey relational analysis to assess the performance of TBM main bearings. Demonstrates applicability through experimental validation using a full-scale test bench.
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Load characterization of the main bearing of a large tunnel boring machine based on dynamic characteristic parameters
Tribology International, (Volume and issue pending confirmation)
Summary: Investigates the dynamic loading behavior of TBM main bearings under actual working conditions, emphasizing transient effects and fatigue life estimation.
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Tribological and dynamical analysis of a brake pad with multiple blocks for a high-speed train
Wear, (Volume and issue pending confirmation)
Summary: Analyzes multi-block brake pad configurations and their influence on friction, vibration, and wear in high-speed rail systems.
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The influence of friction blocks connection configuration on high-speed railway brake systems performance
Proceedings of the Institution of Mechanical Engineers, Part F: Journal of Rail and Rapid Transit
Summary: Explores how different configurations of brake friction blocks affect braking efficiency, noise, and system stability.
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The effect of damping components on the interfacial dynamics and tribological behavior of high-speed train brakes
Tribology Letters, (Volume and issue pending confirmation)
Summary: Studies the role of damping layers and their influence on friction-induced vibrations and wear patterns in braking systems.
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Brake squeal of a high-speed train for different friction block configurations
Journal of Sound and Vibration, (Volume and issue pending confirmation)
Summary: Provides an experimental and theoretical study on the mechanisms of brake squeal in high-speed trains, with a focus on block configuration.
Conclusion
Dr. Yuanke Wu demonstrates a strong profile characterized by technical innovation, research productivity, and practical impact in the field of TBM main bearing diagnostics and surface science. His work bridges experimental mechanics, digital diagnostics, and industrial application, making him a highly suitable candidate for the Best Researcher Award. Continued expansion of international collaborations and professional visibility will further enhance his already impressive contributions.