Congratulations to Prof Ivan Au on the award of MOE AcRF Tier 1

This project aims at developing a fundamentally new and general theory for tracking and detecting potential changes in structural health monitoring (SHM) of civil engineering structures. Success of the project will provide a rigorous theory with efficient computational methodology for future SHM and smart maintenance applications, enabling systems to make intelligent use of structural models and monitoring data, and to reduce heuristic/ad-hoc human intervention in operation decisions.

The project takes on a series of challenging questions of theoretical and computational nature, e.g., what is a suitable ‘model’ for inference in SHM and how should its properties be parameterised to allow their change to be detected properly, trading off the chance of missed/false detection? How to process information in data efficiently, especially when data size keeps growing during monitoring? A comprehensive research programme is proposed to ensure scientific rigour and impact, making complementary use of synthetic data, laboratory-scale and full-scale (field) data for investigation.