Case Study for Using Open-Source UAV-Deployable Wireless Sensor Nodes for Modal-Based Monitoring of Civil Infrastructure

Abstract

Experimental modal analysis is an important technique used in structural health monitoring to evaluate the dynamic properties of a structure, such as natural frequencies, damping ratios, and mode shapes. There has been an increasing interest in using uncrewed aerial vehicles (UAVs) to perform experimental modal analysis, as they offer several advantages over traditional hardwired sensing systems. UAVs equipped with deployable wireless sensor packages can capture a vast amount of data due to their high mobility, enabling the identification of subtle structural behaviors that would be more challenging to obtain using conventional sensors. This case study focuses on the use of UAV-deployable wireless sensor nodes to perform experimental modal analysis on a pedestrian bridge in use. The objective of this study is to demonstrate the potential for monitoring the dynamic properties of a structure using networks of UAV-deployable sensor packages. The paper reports on the development of an open-source UAV-deployable sensor node designed for autonomous deployment on steel structures. The open-source sensor package is a standalone system that includes independent energy storage along with nonvolatile memory and radio frequency communication capabilities. A high-performance microcontroller is utilized to record and process acceleration data in real-time. Moreover, the microcontroller processes various input/output commands, manages the transmission of status updates, and controls the electropermanent magnet onboard during the docking procedure in combination with the UAV to ensure safe deployment. The case study consists of an experimental approach, using a vibration-based sensing network in conjunction with a structural shaker, to capture the structural dynamics of a pedestrian bridge under forced excitation. The results showed that the UAV-deployable wireless sensor nodes were able to capture accurate and reliable data, enabling the identification of the bridge’s first flexural mode shape. Furthermore, this study provides valuable insights into the challenges and prospects associated with using UAV-deployable sensors for the dynamic modeling of structures in a structural health monitoring framework.