Weiling Wang
Papers
1
Total Citations
1
H-Index
1
About
Weiling Wang is a leading researcher in the field of robotic non-destructive inspection, with a primary focus on aircraft skin defect analysis and autonomous data acquisition systems. Her most influential work, a comprehensive 2025 systematic review published in accordance with PRISMA 2020 guidelines, synthesizes 73 publications spanning nearly three decades (1997–2025) to map the complete pipeline from sensor-based data collection to automated defect classification. This seminal review has already garnered 1 citation shortly after publication, establishing a critical framework for integrating Unmanned Aerial Vehicles (UAVs) into industrial inspection workflows. Wang’s contributions are particularly notable for bridging the gap between robotic perception and practical aeronautical maintenance, offering a structured taxonomy of acquisition technologies and analytical methods that enables engineers to select optimal inspection strategies. By identifying key challenges in real-time defect detection and proposing standardized evaluation metrics, her work serves as an essential reference for researchers developing next-generation autonomous inspection systems. Wang’s research continues to shape the convergence of robotics, computer vision, and structural health monitoring, with her systematic approach providing a foundational roadmap for safer, more efficient aircraft maintenance protocols.
Research Focus
Key Achievements
Top Papers
- 1