A distance coefficient-multi objective information fusion algorithm for optimal sensor placement in structural health monitoring

Optimal sensor placement (OSP) plays a key role in the construction and implementation of an effective structural health monitoring system (SHM). In this study, a novel and effective method named the distance coefficient-multi objective information fusion algorithm (D-MOIF), which is different from the conventional method and easier to be implemented, is developed to select the best sensor location for large-scale structures. An integrated information matrix including mode independence, damage sensitivity and modal strain energy is deduced from the structural motion equation to meet multiple needs of SHM. A European distance derived from the analytic geometry is proposed to overcome the information redundancy between sensors. Based on the principle of information entropy, an optimized objective function is constructed, which could balance the sensitivity and robustness of the algorithm. A computational case of a high arch dam is implemented to demonstrate the effectiveness of the modified algorithm, and three classical evaluation criteria are used to estimate the comparison between the D-MOIF algorithm and four traditional OSP methods. Finally, the optimization of the number of sensors based on different algorithms is discussed in detail. Results indicate that the proposed D-MOIF algorithm could generate more applicable sensor configurations for large-scale structures.