*********************************
There is now a CONTENT FREEZE for Mercury while we switch to a new platform. It began on Friday, March 10 at 6pm and will end on Wednesday, March 15 at noon. No new content can be created during this time, but all material in the system as of the beginning of the freeze will be migrated to the new platform, including users and groups. Functionally the new site is identical to the old one. webteam@gatech.edu
*********************************
Title: Machine Learning-Based Structural Health Monitoring of Concrete Structures using Acoustic Signals
Committee:
Dr. Ying Zhang, Advisor
Dr. Moore, Chair
Dr. Ma
Abstract: The objective of the proposed research is to develop a generalized data-driven approach for the assessment of damage in concrete structures while minimizing the need for labeled data. The preliminary research includes a damage detection model which utilized an autoencoder for anomaly detection and a meta-learning approach which demonstrated the feasibility of a few-shot learning model for damage severity assessment of concrete structures. The proposed research focuses on combining probabilistic learning with meta-learning to provide a prediction of damage severity while taking into consideration the uncertainty of measurements.
