Optimal sensor placement for dynamic model updating of civil engineering structures - Toh, Kelly Jia Li. (2013)
Optimal sensor configuration for a nine-storey shear building model is presented using statistical methodology. The optimal placing of sensors allows measured data that contains the most information for model parameter estimation to be collected. This methodology is useful in damage detection, model updating and localisation applications. Uncertainties such as modelling error, and model uncertainties are taken into account for this method. The optimality criterion for the sensor configuration depends on the entropy information, a unique measure of uncertainty in the parameters of the model. The uncertainty is derived using a Bayesian statistical methodology, in which the value of entropy measure is minimised considering a set of possible sensor configurations. The values of entropy measure is computed using genetic algorithm. Large uncertainties are also considered by using Monte Carlo simulation.