Papers
2
Total Citations
4
H-Index
2
About
Bin Long is a researcher specializing in intelligent welding robotics and advanced manufacturing control systems. His work focuses on enhancing the precision and reliability of automated welding processes through innovative sensing and control methodologies. A key contribution is his development of a multi-information fusion detection method for arc welding robots, which uses adaptive Wiener filtering to extract molten pool contour features from images, overcoming uncertainties that compromise weld quality. This research, published in 2019, has garnered 2 citations, reflecting its niche but foundational role in real-time welding quality control. Additionally, Long has advanced robotic kinematics and control by designing a variable gain PID control scheme for multi-axis welding robots, as detailed in his 2012 paper. This work established direct and inverse kinematic models for three-axis linkage systems, improving operational stability and reliability. Though his citation counts are modest, Long’s contributions are significant for researchers and engineers seeking to integrate computer vision and adaptive control into industrial robotics, laying groundwork for more autonomous and defect-free welding solutions.
Research Focus
Key Achievements
Top Papers
- 1
- 2