Xinyan Qin
Papers
14
Total Citations
284
H-Index
8
About
Xinyan Qin is a leading researcher in the field of intelligent power grid inspection, specializing in the development of autonomous robots and advanced sensing technologies for overhead transmission lines. Her major contributions center on creating novel hybrid flying–walking inspection robots that combine aerial mobility with the ability to walk on power lines, dramatically improving inspection efficiency in complex environments like mountains and forests. She has pioneered the use of LiDAR data from these robots to reconstruct 3D models of power lines and detect critical components, with her foundational papers on autonomous inspection and 3D reconstruction each garnering over 60 citations. More recently, she has advanced deep learning-based fault detection, developing synthetic dataset methods and improved YOLOv5 algorithms that achieve high accuracy despite limited real-world fault images. Her work on multiobjective energy optimization and stability control under wind loads further enhances the practical deployment of these robots. With over 270 total citations across her ten most-cited papers, Qin’s research is instrumental in modernizing power line monitoring, making it safer, more reliable, and adaptable to challenging terrains.
Research Focus
Key Achievements
Top Papers
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