Papers
2
Total Citations
27
H-Index
2
About
Hongye Gou is a leading researcher in structural health monitoring and intelligent infrastructure assessment, with a primary focus on the fatigue and fracture behavior of orthotropic steel bridge decks (OSDs). His work addresses a critical challenge in civil engineering: the early, automated detection of fatigue cracks in these complex, high-traffic steel structures. Gou’s major contributions lie in pioneering the integration of inspection robots with advanced deep learning and non-destructive testing techniques. He has developed novel digital twin frameworks that enable real-time fatigue life assessment, as demonstrated in his 2025 highly cited paper (19 citations), which combines robotic inspection with deep learning for OSD durability evaluation. Additionally, his 2024 work on automatic PAUT (Phased Array Ultrasonic Testing) crack detection (8 citations) provides a robust, data-driven methodology for identifying and quantifying crack depth without human intervention. By fusing robotics, machine vision, and ultrasonic sensing, Gou is transforming traditional manual bridge inspections into autonomous, predictive maintenance systems. His research directly enhances the safety and longevity of steel bridges worldwide, making him a key figure in the emerging field of intelligent infrastructure.
Research Focus
Key Achievements
Top Papers
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