Optimal sensor placement for model updating of civil engineering structures subjected to future dynamic loadings

Making use of statistical approach to figure out the optimal sensor locations of the structure where the sensors can measure the most information of the structure parameters. These structure parameters can show the structure conditions and behaviors. Through measurement, it will help us to update the models, finding the damage areas and localization applications. Since, there are many inevitable uncertainties in the parameters and as well as the measured data, it is necessary to take them into account. Information entropy is a kind of special measurement of the uncertainties in the model parameters and it is used as the requirement for choosing of best sensor locations. To handle the large uncertainties, we make use of the Bayesian statistical methodology. In order to minimize the entropy over sets of combination of sensor locations we use a heuristic algorithm. With large model uncertainties, the optimal sensor configurations will be calculated by entropy measures by Bayesian methodology. This project will use a truss bridge structure with 29 degree of freedom to illustrate in this report.Bachelor of Engineering (Civil