Article (Scientific journals)
Identification of non-stationary dynamical systems using multivariate ARMA models
Bertha, Mathieu; Golinval, Jean-Claude
2017In Mechanical Systems and Signal Processing, 88, p. 166-179
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Keywords :
Time-varying systems; modal identification; vector auto-regressive moving average modeling; basis functions; moving mass problem
Abstract :
[en] This paper is concerned by the modal identification of time-varying mechanical systems. Based on previous works about autoregressive moving average models in vector form (ARMAV) for the modal identification of linear time invariant systems, and time-varying autoregressive moving average models (TV-ARMA) for the identification of nonstationary systems, a time-varying ARMAV (TV-ARMAV) model is presented for the multivariate identification of time-varying systems. It results in the identification of not only the time-varying poles of the system but also of its respective time-varying mode shapes. The method is applied on a time-varying structure composed of a beam on which a mass is moving.
Disciplines :
Aerospace & aeronautics engineering
Mechanical engineering
Author, co-author :
Bertha, Mathieu ;  Université de Liège > Département d'aérospatiale et mécanique > LTAS - Vibrations et identification des structures
Golinval, Jean-Claude  ;  Université de Liège > Département d'aérospatiale et mécanique > LTAS - Vibrations et identification des structures
Language :
English
Title :
Identification of non-stationary dynamical systems using multivariate ARMA models
Publication date :
01 May 2017
Journal title :
Mechanical Systems and Signal Processing
ISSN :
0888-3270
eISSN :
1096-1216
Publisher :
Elsevier, Atlanta, Georgia
Volume :
88
Pages :
166-179
Peer reviewed :
Peer Reviewed verified by ORBi
Available on ORBi :
since 28 November 2016

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