Yaqiang Gong

China University of Mining and Technology

Papers

Total Citations

H-Index

About

Yaqiang Gong is a researcher specializing in structural health monitoring and non-contact sensing technologies, with a particular focus on vibration measurement and infrastructure assessment. His most cited work, "Monitoring Sluice Health in Vibration by Monocular Digital Photography and a Measurement Robot" (2019), has garnered 13 citations and exemplifies his innovative approach to combining computer vision with robotics for civil engineering applications. Gong's major contributions lie in developing cost-effective, remote monitoring solutions that replace traditional sensor-based methods with digital photography and robotic platforms, enabling safer and more efficient inspections of critical infrastructure like sluices and bridges. His research integrates monocular vision algorithms with autonomous measurement robots to capture high-precision vibration data, addressing challenges in dynamic structural analysis. While his citation count reflects a growing recognition in the field, his work is notable for its practical implications—offering scalable alternatives for aging infrastructure management. By bridging computer vision, robotics, and structural engineering, Gong is advancing the frontier of intelligent monitoring systems, making his research particularly relevant for students and professionals exploring non-invasive, automated approaches to civil infrastructure health assessment.