Yu-Wei Sun
Papers
1
Total Citations
2
H-Index
1
About
Yu-Wei Sun is a researcher focused on intelligent power systems and machine vision applications for smart substations. His work centers on enhancing automation and safety in electrical infrastructure through computer vision and edge feature extraction techniques. Sun’s most notable contribution is his 2019 study on power cabinet door-opening state recognition, which developed a monocular vision-based method for detecting door status using edge features—a critical step toward enabling autonomous patrol robots to monitor substation equipment reliably. While his citation count remains modest, this foundational work addresses a practical challenge in the transition to smarter, more automated power grids. Sun’s research sits at the intersection of robotics, image processing, and energy systems, aiming to reduce human intervention in hazardous environments. His efforts contribute to the broader goal of creating fully intelligent substations where machines can perform routine inspections and safety checks with high precision. For students and researchers exploring applied computer vision in industrial settings, Sun’s work offers a concrete example of how edge detection algorithms can solve real-world operational problems in critical infrastructure.
Research Focus
Key Achievements
Top Papers
- 1