Shengli Fan
Papers
1
Total Citations
5
H-Index
1
About
Shengli Fan is a researcher whose work sits at the intersection of computer vision and industrial automation, with a particular focus on welding process optimization. His most cited paper, "A Quick Algorithm to Track Welding Line Based on Computer Vision" (2009, 5 citations), introduces a novel framework for real-time welding line tracking in TIG welding applications. The algorithm integrates edge detection using the Prewitt operator, image binarization, target area segmentation, and precise localization of both the welding torch and the welding line, enabling automated guidance in pipe and tube welding. This contribution addresses a critical challenge in manufacturing: achieving accurate, high-speed visual feedback for robotic welding systems. While Fan’s citation count reflects a specialized niche, his work is foundational for researchers developing cost-effective, vision-based control systems in industrial robotics. His approach demonstrates how classical computer vision techniques can be adapted for real-time, high-precision tasks, offering a practical solution for improving weld quality and reducing human error in automated production lines.
Research Focus
Key Achievements
Top Papers
- 1A Quick Algorithm to Track Welding Line Based on Computer Vision5 citations · 2009