Joud Satme

Date of Award

Fall 2023

Document Type

Open Access Thesis

Department

Computer Science and Engineering

First Advisor

Austin Donwey

Abstract

Natural disasters and extreme weather events pose significant threats to the structural integrity and safety of civil and environmental infrastructure. In this context, Structural Health Monitoring (SHM) emerges as a pivotal discipline, intersecting engineering, technology, and disaster resilience. SHM's mission is to provide real-time, data-driven insights into the condition of critical infrastructure, encompassing bridges, buildings, dams, and transportation networks. These systems not only expedite assessment, but also wield substantial influence in mitigating catastrophic disasters. As the frequency and intensity of extreme weather conditions escalate due to climate change, the need for robust and proactive SHM strategies becomes increasingly apparent. Moreover, the continuous monitoring of structures in dynamic environments necessitates more versatile solutions. Traditionally, SHM relied on wired systems, laden with logistical complications and steep installation costs, particularly in remote or challenging locations. Unmanned aerial vehicles (UAVs) and wireless technologies have revolutionized rapid SHM, promising groundbreaking advancements in the way structures are evaluated and secured. Deploying wireless systems for rapid SHM confronts the intricate challenge of optimizing sensor placement while maintaining a robust connection. Furthermore, signal deterioration due to transmissibility loss and the imperative of low-power signal detection in sensing systems compound these challenges. An extensive report of the aerial deployment design, development procedure, and strategies employed to enhance the onboard vibration sensor's signal-to-noise ratio is provided. These enhancements are achieved through the integration of lightweight 3D printed materials, small footprint low-power electronics, and the implementation of a machine learning-based Long Short-Term Memory (LSTM) error compensator. Deliverables of this work include 1) An overview of the aerial deployment and retrieval system via electropermanent magnets integrated into uncrewed aerial vehicles. 2) A breakdown of the sensor hardware and onboard subsystems. 3) A comprehensive report of the algorithm employed to combat signal degradation due to mechanical transmissibility loss. Finally, 4) a general view of the wireless system with a focus on network communication, low-latency wireless triggering, and transmission error-handling. The focus remains on enhancing structural safety, resilience, and adaptability, ultimately safeguarding critical infrastructure for a more secure and sustainable future.

Rights

© 2024, Joud Satme

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