Proper orthogonal decomposition for model updating of non-linear mechanical systems

Proper orthogonal decomposition (POD), also known as Karhunen-Loeve (K-L) d ecomposition, is emerging as a useful experimental tool in dynamics and vib rations. The POD is a means of extracting spatial information from a set of time-series data available on a domain. The use of(K-L) transform is of gr eat help in non-linear settings where traditional linear techniques such as modal-testing and power-spectrum analyses cannot be applied. These decompo sition can be used as an orthogonal basis for efficient representation of t he ensemble. The POM have been interpreted mainly as empirical system modes and the application of POD to measured displacements of a discrete structu re with a known mass matrix leads to an estimation of the normal modes. We investigate the use of the proper orthogonal modes of displacements for the identification of parameters of non-linear dynamical structures with an op timisation procedure based on the difference between the experimental and s imulated POM. A numerical example of a beam with a local non-linear compone nt will illustrate the method. (C) 2001 Academic Press.