Andrew George

Physics-Informed Machine Learning and Multi-Sensor Fusion for Structural Health Monitoring: A Bridge Case Study

Guga Gugaratshan, A. Halfpenny, F. Kihm, Cristina Barbosa, Sarah Miele, Andrew George

TL;DR: Results show that multi-year monitoring data can be reduced into compact fatigue-relevant features while preserving traceability to raw measurements, and a supervisory agentic layer coordinates data-quality checks, multi-sensor consistency review, and confidence-tagged substitution, creating an auditable workflow for engineering decision support.

Ensuring the integrity of critical infrastructure, such as bridges, dams, and large-scale structures, is essential to safety, reliability, and operational continuity. These assets are exposed to mechanical, thermal, environmental, and operational loads that can accelerate fatigue…Read more