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3D Printable RFID Embedded Damage Sensors For Structural Health Monitoring

thesis
posted on 2024-07-26, 03:04 authored by Metin Pekgor
This research presents ground-breaking advancements in Structural Health Monitoring (SHM) through innovative RFID integration. Novel 3D-printable RFID-embedded filaments promise scalable, resilient sensors, streamlining SHM. Advanced techniques, using the MUSIC algorithm, machine learning, and enhanced RFID sensitivity via photoluminescence materials, revolutionize damage detection and localization with the 3D printing encapsulation of the passive RFID sensors. By these sensors, unique non-destructive testing of fiber-reinforced polymers, facilitated by deep learning, promises accurate, cost-effective manufacturing defect detection. Together, these innovations mark transformative strides in structure safety, smart city applications, and manufacturing efficiency.

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Thesis type

  • Thesis (PhD)

Thesis note

Thesis submitted for the Degree of Doctor of Philosophy, Swinburne University of Technology, 2023.

Copyright statement

Copyright © 2023 Metin Pekgor.

Supervisors

Mostafa Nikzad

Language

eng

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