Tongtong Yan
Papers
1
Total Citations
3
H-Index
1
About
Tongtong Yan is a leading researcher in mechanical reliability and industrial robotics, with a primary focus on the performance degradation and fault diagnosis of critical transmission components. His most cited work, "Performance degradation assessment methodology of harmonic reducer by using low-frequency time series data and genetic programming" (2021), introduces an innovative approach that leverages low-frequency time series data and genetic programming to monitor and predict the health of harmonic reducers—key components in industrial robots that determine positioning accuracy and service life. This methodology offers a cost-effective, data-driven solution for early failure detection, directly addressing the challenge of maintaining robot reliability under prolonged operation. With 3 citations, this paper has already influenced subsequent studies in predictive maintenance and condition monitoring. Yan’s contributions are vital for advancing the longevity and safety of automated manufacturing systems, and his work continues to shape best practices in mechanical component assessment.
Research Focus
Key Achievements
Top Papers
- 1