Optimal sensor placement for dynamic model updating of civil engineering structures - Chin, Khee Hoo. (2013)
A statistical methodology is presented to determine the optimal sensor locations in a structure for the purpose of extracting the most informative measure data about the model parameters which are used to represent the performance of the structure. Besides that, the methodology also used in model updating, response prediction, detection of damage and its localization. The selection of the optimal sensor locations is based on an information entropy contained measurement of the uncertainty in the mode. This methodology can properly handle the unavoidable uncertainties in model parameter and the prediction accuracy. These uncertainties are computed by Bayesian Methodology, while the optimal sensor locations are determined by reducing the entropy measure over all possible sensor configurations. The information entropy measure is then extended to handle the large model uncertainties, where the equation is being modified to account for all the possible value of predicted parameters. The optimal sensor locations for large model uncertainties case are also being determined. Evaluation of the improvement in model updating performance is being done when the number of sensors located at their optimal location is raised. The methodology is illustrated by a nine DOFs building represent by a mass-spring model.