Zhuanzhe Zhao
Papers
2
Total Citations
18
H-Index
2
About
Zhuanzhe Zhao is a researcher focused on mechanical fault diagnosis and intelligent control systems, with particular expertise in rotating machinery and robotic thermal management. His most cited work, “Rotate Vector Reducer Fault Diagnosis Model Based on EEMD-MPA-KELM” (2023, 14 citations), introduces a novel hybrid approach combining Ensemble Empirical Mode Decomposition with Marine Predators Algorithm-optimized Kernel Extreme Learning Machine to accurately assess RV reducer health states—a critical contribution to predictive maintenance in industrial robotics. Zhao’s research addresses the challenge of irregular rotation periods in aging machinery, demonstrating how advanced signal processing can capture subtle periodic anomalies. In complementary work, “Design and simulation analysis of physical heat dissipation structure for welding robot controller” (2023, 4 citations), he tackles thermal management challenges in automated welding systems through computational modeling of heat dissipation structures. Zhao’s contributions bridge theoretical signal processing with practical industrial applications, offering cost-effective solutions for extending equipment lifespan. His work is particularly valuable for engineers developing condition monitoring systems in manufacturing, where early fault detection can prevent costly downtime.
Research Focus
Key Achievements
Top Papers
- 1Rotate Vector Reducer Fault Diagnosis Model Based on EEMD-MPA-KELM14 citations · 2023
- 2