Julong Song

Nanjing University of Posts and Telecommunications

Papers

Total Citations

H-Index

About

Julong Song is a robotics researcher specializing in structural health monitoring and intelligent inspection systems for large-scale civil infrastructure. His primary research areas include cable-detecting robots, adaptive loading mechanisms, and non-destructive evaluation techniques for bridge cables. Song’s major contributions lie in enhancing the climbing stability of cable-inspection robots under dynamic cable vibrations. He pioneered a coupled loading–damping mechanism that integrates variable stiffness and damping control, significantly improving robot adhesion and detection reliability on cable-stayed bridges. His work on combining computer vision with diameter measurement for automated surface damage detection, and his study of magnetic flux leakage for broken wire detection during spiral climbing, have advanced practical bridge maintenance. With over 13 citations across his most-cited papers, Song’s research directly addresses critical safety challenges in aging infrastructure. His 2024 paper on the coupled loading–damping mechanism, with 7 citations, represents a notable achievement in adaptive robotic control for real-world structural inspection. Song’s work is essential reading for researchers and engineers developing autonomous systems for high-risk, high-reward infrastructure monitoring tasks.