Chiheng Huang

University of Huddersfield

Papers

1

Total Citations

2

H-Index

1

About

Chiheng Huang is a researcher focused on advancing industrial robotics and intelligent fault detection systems. His work centers on enhancing the reliability and safety of collaborative robots, particularly through the development of real-time diagnostic methods for abnormal joint behavior. In his notable 2024 paper, "Residual-Based Fault Detection of Abnormal Joint Running State of Industrial Collaborative Robot," Huang introduced a novel approach that leverages residual analysis to identify mechanical anomalies before they escalate into critical failures. This contribution is vital for industries relying on human-robot collaboration, where early fault detection can prevent costly downtime and ensure operator safety. Although his research is still emerging, with this paper accumulating 2 citations to date, Huang’s work demonstrates a strong potential for impact in the field of industrial automation. His focus on practical, implementable solutions positions him as a promising voice in the ongoing effort to make collaborative robots more autonomous, efficient, and trustworthy in real-world manufacturing environments.

Research Focus

Key Achievements

1
H-Index
1
Papers
2
Total Citations
2
Avg Citations/Paper
🏆 Most Cited Paper
Residual-Based Fault Detection of Abnormal Joint Running State of Industrial Collaborative Robot
2 citations · 2024
📈 Most Prolific Year: 2024 (1 Papers)
🤝 Key Collaborators: 6
🏛 Institutions: University of Huddersfield

Top Papers

  1. 1

Key Collaborators

Contact & Links

Available for collaboration
Content generated · 12 days ago