Thesis Defense Flyers
Development and Testing of a Prototype
Erbium-Doped Lithium Tantalate Based Sensor
for UAV Infrastructure Crack Detection
Chairs: Dr. Constantine Tarawneh, Dr. Farid Ahmed
Members: Dr. Heinrich Foltz, Dr. Arturo Fuentes
Ensuring the safety and longevity of infrastructure is crucial to safeguarding communities and
preserving economic stability. In this study, we present the development of a novel sensor for
detecting and characterizing cracks in infrastructure, particularly suited for deployment on
Unmanned Aerial Vehicles (UAVs). The device...
Feature Extraction from Railroad Bearing
Onboard Vibration Sensors Using Machine
Learning Models
Chairs: Dr. Constantine Tarawneh, Dr. Ping Xu
The railway industry faces approximately 1,000 train derailments annually, highlighting the insufficiency of
traditional condition monitoring and maintenance methods. To address this, advanced artificial intelligence (AI)
and machine learning (ML) algorithms were developed and implemented, leveraging vibrational data collected
by the University Transportation Center for Railway Safety (UTCRS). Using...
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