Xiang‐Qian Chang
Papers
1
Total Citations
9
H-Index
1
About
Xiang-Qian Chang has made significant contributions to intelligent manufacturing, with a primary focus on advancing robotic welding technology through artificial intelligence. His research centers on welding seam recognition, a critical component for enabling autonomous welding robots to achieve high precision and efficiency. Chang’s most notable work, "Welding Seam Recognition Technology of Welding Robot Based on A Novel Multi-Path Neural Network Algorithm" (2022), introduces a groundbreaking approach that leverages a multi-path neural network to dramatically improve the accuracy and reliability of seam detection. This innovation addresses the limitations of traditional algorithms, which are far inferior in complex, real-world welding environments. By integrating independent planning, seam position detection, and automatic tracking, his research directly enhances the autonomy of welding robots, reducing human error and increasing productivity. With 9 citations, this paper has already garnered attention from peers in robotics and manufacturing, underscoring its practical impact. Chang’s work stands at the intersection of deep learning and industrial automation, offering a scalable solution for modern fabrication. His achievements highlight a commitment to bridging theoretical AI advances with tangible, real-world applications, making him a key figure in the evolution of smart manufacturing systems.
Research Focus
Key Achievements
Top Papers
- 1