Modal identification and damage detection using the data-driven stochastic subspace and ARMAV methods

This paper presents results of modal identification and damage detection on the Steel-Quake structure using the autoregressive moving average vector and data-driven stochastic subspace methods. The methods directly work with the recorded time signals and allow to analyse linear systems where only the system output is measured, while the input is unknown but produced by uncorrelated random signals. These techniques can also be used directly to analyse data obtained from the free response of linear systems. (C) 2003 Elsevier Science Ltd. All rights reserved.