Optimal maintenance decisions supported by SHM: A benchmark study

Despite technological advancements, visual inspection still remains the primary, and oftentimes sole, means for condition-based assessment, in the current approach to infrastructure operation and maintenance. Structural Health Monitoring (SHM) may be exploited as a complementary source of information on the condition of a system. However, it is currently difficult to quantify the effect of SHM on optimal operation and maintenance and hence on the total life-cycle cost. As a step towards this goal, we employ a numerical benchmark for continuous monitoring under operational variability (Tatsis & Chatzi, 2019). The numerical benchmark serves as a tool to create reference monitoring data from a two-span bridge system subject to deterioration (local stiffness reduction) over its lifespan. The benchmark is used as a simulator for extracting dynamic response data, i.e. simulated measurements (accelerations), corresponding to a typical deployment on the structure. At each time step, Bayesian updating of the deterioration model and the structural reliability is carried out, using the modal data stemming from an operational modal analysis. The reliability updating is the basis for a preposterior decision analysis, to evaluate the Value of Information (VOI) of the SHM system (Straub et al., 2017). For that, a decision time step, an action and the corresponding costs are defined. A heuristic-based approach using a simple decision rule is employed for life-cycle optimization. The resulting expected life-cycle costs are computed for the case of the deployed SHM system, and compared against the expected life-cycle costs obtained in the case of no information, thus enabling the quantification of the VOI of SHM.