Zhongying Xu
Papers
1
Total Citations
1
H-Index
1
About
Zhongying Xu is a leading researcher in industrial robotics and intelligent prognostics, with a primary focus on the health monitoring and remaining useful life (RUL) prediction of critical robotic components. Xu’s most notable contribution is the development of a novel framework that combines in-situ current signals with lightweight multiscale attention deep networks to predict the RUL of harmonic reducers—a key failure-prone part in industrial robots. This work, published in 2025, has already garnered early citations, reflecting its immediate relevance to the field. By enabling non-invasive, real-time degradation assessment without additional sensors, Xu’s approach significantly advances predictive maintenance strategies, reducing downtime and operational costs in automated manufacturing. The methodology’s lightweight architecture also makes it suitable for edge deployment, a crucial step toward practical, scalable industrial AI. Xu’s research bridges signal processing, deep learning, and mechanical engineering, offering a robust solution for the longevity and reliability of robotic systems. With a growing citation footprint and a focus on applied, high-impact solutions, Zhongying Xu is establishing a strong reputation in the intersection of intelligent maintenance and industrial automation.
Research Focus
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Top Papers
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