Foundation Models for Structural Health Monitoring

arXiv:2404.02944v1 Announce Type: new
Abstract: Structural Health Monitoring (SHM) is a critical task for ensuring the safety and reliability of civil infrastructures, typically realized on bridges and viaducts by means of vibration monitoring. In this paper, we propose for the first time the use of Transformer neural networks, with a Masked Auto-Encoder architecture, as Foundation Models for SHM. We demonstrate the ability of these models to learn generalizable representations from multiple large datasets through self-supervised pre-training, which, coupled with task-specific …

abstract architecture arxiv auto civil cs.ai cs.lg cs.sy eess.sy encoder foundation health monitoring networks neural networks paper reliability safety transformer type