Optimal sensor and actuator placement for structural health monitoring via an efficient convex cost-benefit optimization

The number and position of sensors and actuators are key decision variables that dictate the performance of any structural health monitoring system. This paper proposes choosing them optimally by using an objective function that combines a measure of parameter uncertainty, the expected information entropy, along with the cost of both sensors and actuators. The resulting optimization problem over discrete decision variables is computationally challenging, but here it is convexified by relaxing them into continuous variables, thus obtaining a significant reduction of the computational cost. The proposed approach is applied to ultrasonic guided-wave based inspection and is illustrated using two case studies with arbitrary geometries and different materials. The results demonstrate the high efficiency and accuracy of the convex optimization in trading-off uncertainty and cost in order to provide optimal sensor configurations in complex structures. As a key contribution, the proposed methodology allows us to include the actuators with the sensors in the optimization problem while still maintaining the efficiency of the minimization process. In the application to ultrasonic guided-waves, the optimal configurations lead to set-ups where the sensors and actuators are coincident in number and position.