Minghao Fan
Papers
1
Total Citations
7
H-Index
1
About
Minghao Fan is a researcher focused on advancing intelligent inspection technologies for power systems, with key contributions in computer vision and defect recognition. His most cited work, "Research on Cable Defect Recognition Technology Based on Image Contour Detection" (2021, 7 citations), addresses the critical challenge of automating cable trench inspections in complex environments. Fan developed a cable defect identification system that integrates an insulation layer damage detection algorithm with temperature anomaly analysis, enabling robust, real-time monitoring of power infrastructure. This work directly supports the reliability and safety of electrical grids by reducing reliance on manual inspections. While his citation count is still growing, Fan’s research demonstrates practical impact in the niche but essential field of power system maintenance. His approach—combining contour detection with multi-modal sensing—offers a scalable solution for detecting subtle defects that could lead to failures. For students and researchers in electrical engineering and computer vision, Fan’s work exemplifies how targeted algorithmic design can solve real-world industrial problems, bridging the gap between laboratory research and operational deployment in critical infrastructure.
Research Focus
Key Achievements
Top Papers
- 1