Optimal sensor configuration of a typical transmission tower for the purpose of structural model updating

Abstract

A methodology is presented for the identification of the best locations to install a given number of sensors on a structure so as to extract as much information as possible for structural model updating. The information entropy measure is employed to quantify the uncertainties of the set of identified model parameters. The problem of optimal sensor placement is formulated as a discrete optimization problem in which the information entropy measure is minimized and the sensor configurations are taken as the minimization variables. This discrete optimization problem is computationally demanding especially for large-scale structures. An efficient genetic algorithm-based optimization method is developed to solve this minimization problem to make the entropy-based optimal sensor configuration approach applicable for large-scale structural systems. A typical transmission tower is first used as a numerical example to illustrate the proposed methodology. The performance of the optimal sensor placement technique and the proposed optimization method are then verified using the measured dynamic data from a 2.6 m high transmission tower model under laboratory conditions. The computational time of the proposed optimization method can be reduced in the future by making use of the parallel computing technology. Copyright © 2009 John Wiley & Sons, Ltd.