Bridge Information Modelling Supported Structural Health Diagnosis and Prognosis Using On-site Strain Data

This research develops a new bridge monitoring approach that uses strain data, the stretching and compression of materials, to assess structural health. Unlike traditional visual inspections, it enables continuous, data-driven evaluation. Using a real reinforced concrete bridge in New South Wales, the study introduces a strain-based feature for detecting damage, evaluates fatigue in concrete and steel, and incorporates uncertainty analysis through fuzzy logic. A digital bridge model links sensor data with visual results, improving understanding and communication. The framework supports safer, smarter, and more cost-effective maintenance for long-term bridge management and predictive infrastructure planning.