Haitao Yuan

Nanchang University, Hefei University of Technology

Papers

Total Citations

H-Index

About

Haitao Yuan is a leading researcher in intelligent manufacturing and robotic welding, with a primary focus on real-time weld quality monitoring and defect detection. His work addresses a critical challenge in automated production: accurately identifying weld defects in galvanized steel, where high-temperature zinc vapor complicates traditional sensing. Yuan’s most impactful contribution is the development of a visual sensing-assisted monitoring method for gas metal arc welding (GMAW), achieving 37 citations. He further advanced this field by integrating a random forest model for active, real-time detection of weld surface defects, a paper that has garnered 22 citations. This work demonstrates a practical, data-driven approach to improving robotic welding reliability. Beyond welding, Yuan has explored flexible tactile sensor arrays for robot skin, using carbon nanotubes to create tension-pressure sensors. His research bridges sensor technology and machine learning to solve industrial manufacturing problems, directly impacting production quality and automation efficiency. With a growing citation record, Yuan is establishing himself as a key innovator in smart manufacturing and process monitoring.