Structural Health Monitoring in Bridge Management System

<p dir="ltr">Like all engineered structures, road bridges deteriorate over time due to corrosion, repeated traffic loadings, environmental effects, and natural hazards such as floods and earthquakes. As vital links in Australia’s transport network, their structural integrity has traditionally been monitored through scheduled in-person inspections. Bridge assets are scheduled for inspections every two to five years unless a significant defect or abnormal condition is detected. The rapid increase in traffic, particularly from heavy vehicles, is accelerating the deterioration rate and reducing the service life of bridges concurrently. Although this traditional regime provides a safe network, it lacks predictive capability and is costly to maintain. Therefore, developing a comprehensive management system is essential to optimise resource allocation and support long-term maintenance planning. </p><p dir="ltr">In recent years, the Structural Health Monitoring (SHM) system has gained significant global prominence for its ability to gather structural response data, manage risks, trigger assessment and maintenance of unsatisfactory underperformed bridges. SHM systems enable organisations and engineers to assess the real-time performance of the bridge structures by continuously or periodically collecting structural response data. This research proposed an advanced Bridge Management System (BMS) framework that integrates SHM system to enable predictive bridge condition and enhance decision-making for bridge networks. An effective BMS comprises five major modules: an Inventory Module, an Inspection Module, a Deterioration Module, a Capacity Assessment Module, and a Maintenance, Repair and Rehabilitation (MR&R) Module. </p><p dir="ltr">In this study, the proposed BMS provides a facility for systematic inspection and management of a network of bridges in Australia. It provides a powerful decision-support tool for the road authorities and asset owners to proactively prioritise maintenance interventions, optimise life-cycle costs, and ultimately ensure the structural safety and serviceability of the infrastructure assets. By incorporating the Markov Chain deterioration model, SHM-based load rating evaluation, and Life-Cycle Cost Analysis, a Multi-objective Index is used to prioritise the maintenance actions in MR&R planning. The proposed system was validated through a case study of the Boronia Road Bridge by providing a data-driven basis for load rating assessments to ensure structural integrity.</p>