Optimal sensor and actuator configuration for structural identification

Abstract

A methodology is presented for designing cost-effective optimal sensor and actuator configurations useful for structural model updating and health monitoring purposes. The optimal sensor and actuator configuration is selected such that the resulting measured data are most informative about the condition of the structure. This selection is based on an information entropy measure of the uncertainty in the model parameter estimates obtained using a statistical system identification methodology. The optimal sensor and actuator configuration is selected as the one that minimizes the information entropy. A discrete optimization problem arises which is solved efficiently using genetic algorithms. This study also addresses important issues related to robustness of the optimal sensor and actuator configuration to unavoidable uncertainties in the structural model, as well as issues related to the optimal sensor and actuator configurations designed to monitor multiple damage scenarios. The theoretical developments are illustrated by designing the optimal configuration for a 40-DOF two-dimensional truss structure subjected to an impulse hammer excitation.