Modal Identification Using OMA Techniques: Nonlinearity Effect
Joint Authors
Zhang, E.
Pintelon, R.
Guillaume, P.
Source
Issue
Vol. 2015, Issue 2015 (31 Dec. 2015), pp.1-12, 12 p.
Publisher
Hindawi Publishing Corporation
Publication Date
2015-07-07
Country of Publication
Egypt
No. of Pages
12
Main Subjects
Abstract EN
This paper is focused on an assessment of the state of the art of operational modal analysis (OMA) methodologies in estimating modal parameters from output responses of nonlinear structures.
By means of the Volterra series, the nonlinear structure excited by random excitation is modeled as best linear approximation plus a term representing nonlinear distortions.
As the nonlinear distortions are of stochastic nature and thus indistinguishable from the measurement noise, a protocol based on the use of the random phase multisine is proposed to reveal the accuracy and robustness of the linear OMA technique in the presence of the system nonlinearity.
Several frequency- and time-domain based OMA techniques are examined for the modal identification of simulated and real nonlinear mechanical systems.
Theoretical analyses are also provided to understand how the system nonlinearity degrades the performance of the OMA algorithms.
American Psychological Association (APA)
Zhang, E.& Pintelon, R.& Guillaume, P.. 2015. Modal Identification Using OMA Techniques: Nonlinearity Effect. Shock and Vibration،Vol. 2015, no. 2015, pp.1-12.
https://search.emarefa.net/detail/BIM-1077982
Modern Language Association (MLA)
Zhang, E.…[et al.]. Modal Identification Using OMA Techniques: Nonlinearity Effect. Shock and Vibration No. 2015 (2015), pp.1-12.
https://search.emarefa.net/detail/BIM-1077982
American Medical Association (AMA)
Zhang, E.& Pintelon, R.& Guillaume, P.. Modal Identification Using OMA Techniques: Nonlinearity Effect. Shock and Vibration. 2015. Vol. 2015, no. 2015, pp.1-12.
https://search.emarefa.net/detail/BIM-1077982
Data Type
Journal Articles
Language
English
Notes
Includes bibliographical references
Record ID
BIM-1077982