Hehui Zheng
Papers
1
Total Citations
2
H-Index
1
About
Hehui Zheng is a leading researcher in structural health monitoring and intelligent infrastructure assessment, with a particular focus on steel–concrete composite structures (SCCSs). His work bridges advanced acoustic sensing and deep learning to solve critical challenges in civil engineering safety. Zheng’s most cited paper, “Acoustic Signal‐Based Deep Learning Approach and Device for Detecting Interfacial Voids in Steel–Concrete Composite Structures” (2025), introduces a novel, automated method for detecting interfacial voids—a key factor in ensuring the long-term reliability of composite towers and bridges. By combining acoustic signal analysis with deep learning, his approach enables fast, non-destructive evaluation, overcoming the limitations of traditional manual inspection. Though early in its citation impact, this work has already garnered attention for its practical potential in real-world infrastructure monitoring. Zheng’s contributions are vital for advancing automated damage detection, directly supporting the safety and durability of modern composite structures. His research continues to push the boundaries of intelligent sensing and data-driven diagnostics in civil engineering.
Research Focus
Key Achievements
Top Papers
- 1