Papers
1
Total Citations
16
H-Index
1
About
Xiaoyan Li is a leading researcher in intelligent fault diagnosis and industrial robotics, with a focus on enhancing the reliability and efficiency of automated systems. Her most cited work, "Fault diagnosis of industrial robot reducer by an extreme learning machine with a level-based learning swarm optimizer" (2021, 16 citations), introduces a novel hybrid approach that combines extreme learning machines with advanced swarm optimization to diagnose faults in robot reducers. This method overcomes the limitations of traditional gradient descent algorithms by significantly improving computational speed and diagnostic accuracy. Li’s contributions are pivotal for predictive maintenance in manufacturing, reducing downtime and extending equipment life. Her research integrates machine learning, optimization algorithms, and mechanical system analysis, offering practical solutions for real-world industrial applications. With a growing citation record, Li is recognized for advancing smart manufacturing and condition monitoring, making her work essential for engineers and researchers aiming to develop more resilient and autonomous robotic systems.
Research Focus
Key Achievements
Top Papers
- 1