[en] 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.
Disciplines :
Mechanical engineering
Author, co-author :
Bodeux, Jean-Bernard
Golinval, Jean-Claude ; Université de Liège - ULiège > Département d'aérospatiale et mécanique > LTAS - Vibrations et identification des structures
Language :
English
Title :
Modal identification and damage detection using the data-driven stochastic subspace and ARMAV methods
Publication date :
January 2003
Journal title :
Mechanical Systems and Signal Processing
ISSN :
0888-3270
eISSN :
1096-1216
Publisher :
Academic Press Ltd Elsevier Science Ltd, London, United Kingdom
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