Deep Learning-based Methods for Structural Health Monitoring Data Improvement and Augmentation
This thesis addresses data quality challenges in Structural Health Monitoring (SHM) using deep learning techniques. A Transformer-based generative adversarial network is developed to reconstruct missing signal. An unsupervised domain adaptation-based methodology is proposed to impute missing data. A...
| Main Author: | |
|---|---|
| Format: | Thesis |
| Published: |
Curtin University
2024
|
| Online Access: | http://hdl.handle.net/20.500.11937/97309 |