Lanzhou Jiaotong University | China
Mr. Yucen Yuan is an early-career researcher affiliated with Lanzhou Jiaotong University, China, with a focused research profile in intelligent fault diagnosis and data-driven condition monitoring of renewable energy systems. His work lies at the intersection of machine learning, optimization algorithms, and mechanical fault detection, with particular emphasis on wind turbine bearing health assessment. Yuan has authored 2 peer-reviewed publications, accumulating 1 citation to date and 1 h-index, reflecting emerging scholarly visibility. His 2025 article in Engineering Research Express introduces an improved dung beetle optimizer–enhanced LSTM framework, demonstrating methodological innovation in time-series fault diagnosis. This contribution highlights his expertise in deep learning optimization, signal analysis, and industrial predictive maintenance. Yuan has engaged in collaborative research, contributing as part of a small co-author network, and his work supports the reliability and sustainability of wind energy infrastructure. The societal impact of his research aligns with global clean energy goals by advancing intelligent monitoring technologies that reduce equipment failure, maintenance costs, and operational risks in renewable power systems.
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