3D Printable RFID Embedded Damage Sensors For Structural Health Monitoring
thesis
posted on 2024-07-26, 03:04authored byMetin 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.
History
Thesis type
Thesis (PhD)
Thesis note
Thesis submitted for the Degree of Doctor of Philosophy, Swinburne University of Technology, 2023.