Lerui Chen
Papers
1
Total Citations
4
H-Index
1
About
Lerui Chen is a researcher advancing the reliability and intelligence of industrial robotic systems, with a primary focus on fault diagnosis and nonlinear dynamics in closed-loop drive systems. His most-cited work, "Fault mechanism analysis and diagnosis for closed-loop drive system of industrial robot based on nonlinear spectrum" (2022), addresses a critical gap in fault diagnosis research by proposing a novel method that leverages nonlinear spectrum analysis. This approach overcomes the limitations of traditional linear methods, which often neglect nonlinear characteristics and lack robust fault mechanism analysis. By integrating the Permanent Magnet Synchronous Motor (PMSM) model, Chen’s work provides a more accurate framework for detecting and diagnosing faults in robotic drive systems, directly enhancing operational safety and maintenance efficiency. With 4 citations, this paper has already influenced peers in the field of industrial automation and mechatronics. Chen’s contributions are particularly notable for their practical relevance to modern manufacturing, where robot reliability is paramount. His research continues to bridge theoretical nonlinear dynamics with real-world engineering challenges, marking him as an emerging voice in intelligent fault diagnosis and robotic system health management.
Research Focus
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Top Papers
- 1