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Non-Contact Vibration-Based Damage Detection of Civil Structures Using a Cost-Effective Autonomous UAV

arXiv:2605.2191442.1
Predicted impact top 51% in RO · last 90 daysOriginality Synthesis-oriented
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For civil infrastructure monitoring, this work provides a practical and scalable solution for damage detection in scenarios where contact-based sensing is impractical.

This paper presents a non-contact vibration-based damage detection method using a low-cost autonomous UAV. Experimental results show the UAV reliably detects damage-induced frequency shifts with up to 5.7% error, offering comparable performance to commercial systems at lower cost.

This paper presents a non-contact approach for vibration-based structural damage detection using an autonomous and customized cost-effective unmanned aerial vehicle (UAV). Vibration signals are extracted from video recordings through vision-based motion tracking to identify shifts in natural frequencies indicative of structural degradation. A laboratory-scale frame structure is evaluated under healthy and simulated-damage conditions. The proposed system is validated through an experimental study involving two smartphones, a USB camera, and a custom-built low-cost UAV equipped with an onboard camera and an autonomous alignment system for operation in GPS-denied environments. The displacement time is extracted and analyzed in the frequency domain and compared to reference measurements from contact accelerometers and a finite element model. Experimental results show that all platforms successfully capture the fundamental frequency and its shift due to damage. Although the UAV exhibits slightly higher errors (up to 5.7%) due to platform-induced disturbances and sensing limitations, it reliably detects damage-induced frequency changes. Compared to commercial UAV systems, the proposed platform achieves comparable inspection performance at significantly lower cost. These results demonstrate that low-cost autonomous UAVs provide a practical, flexible, and scalable solution for structural health monitoring, particularly in scenarios where contact-based sensing is impractical. The findings also support the potential for the deployment of multiple cooperative UAVs to further enhance inspection coverage and robustness.

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