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Optimal Decision Making for Cost-effective SHM Planning



This paper investigates the optimal decision making for cost-effective structural health monitoring (SHM) planning. The uncertainty of the monitoring data is represented by the availability. The prediction error between the actual value of parameter and monitored parameter is considered in the formulation of the availability of monitoring data. Based on the availability of monitoring data with the loss estimation, the decision making is applied to find the best alternative associated with SHM planning. In this decision making, the expected monetary values (EMV) of all the possible alternatives are computed and compared. As a result, the alternative with the maximum EMV leads to the best cost-effective SHM plan, which provides the optimum monitoring and prediction durations. Furthermore, in order to integrate the uncertainty associated with the damage occurrence and propagation into the decision making for optimum SHM planning, the expected damage detection time and delay are estimated. The optimum SHM plan is obtained by solving the optimization problem to minimize the expected damage detection time and delay. Finally, SHM starting times are optimized.


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