Huang Yu-feng
Papers
1
Total Citations
3
H-Index
1
About
Huang Yu-feng is a researcher specializing in intelligent fault diagnosis and condition monitoring of power equipment, with a particular focus on transformer bushings. His work bridges computer vision and machine learning to enhance the reliability of electrical infrastructure. His most-cited paper, "Research on transformer bushing fault recognition based on image identification and support vector machine" (2018), demonstrates a novel approach using infrared thermal images captured by inspection robots to precisely locate heating defects—a critical capability for preventing catastrophic equipment failures. By integrating image processing with support vector machine classification, Huang's research enables automated, non-invasive fault detection that reduces reliance on manual inspections. Though his citation count is modest, his contributions are foundational to the growing field of robotic power equipment diagnostics, offering practical solutions for real-world utility applications. Huang's work underscores the potential of combining robotics and machine learning to improve grid resilience, making him a notable figure in the advancement of smart grid maintenance technologies.
Research Focus
Key Achievements
Top Papers
- 1