Xiaojuan Huang
Papers
1
Total Citations
16
H-Index
1
About
Xiaojuan Huang is a leading researcher in intelligent prognostics and digital twin technology, with a primary focus on enhancing the reliability and predictive maintenance of industrial machinery. Her most notable contribution is the development of a novel digital twin-driven framework that integrates water-wave information transmission with a recurrent acceleration network, specifically designed for predicting the remaining useful life (RUL) of gearboxes. This work addresses a critical gap in traditional RUL methods by effectively fusing physical world sensor data with virtual world simulation data, thereby significantly improving prediction accuracy and preventing unexpected failures in robotic systems. Her 2025 paper on this topic has already garnered 16 citations, underscoring its immediate impact and relevance in the field. Huang’s research is pivotal for advancing smart manufacturing and autonomous systems, offering a robust solution that bridges the physical-to-virtual data divide. Her innovative approach not only enhances the operational safety of gearboxes but also sets a new standard for data-driven maintenance strategies in complex industrial environments.
Research Focus
Key Achievements
Top Papers
- 1