Application of the proper orthogonal decomposition for linear and nonlinear structures under transient excitations

2012 ◽  
Vol 223 (12) ◽  
pp. 2549-2563 ◽  
Author(s):  
F. Bamer ◽  
C. Bucher
Keyword(s):  
Proper Orthogonal Decomposition ◽  
Orthogonal Decomposition ◽  
Nonlinear Structures ◽  
Linear And Nonlinear ◽  
Proper Orthogonal

System Identification Techniques for Mixed Responses Using the Proper Orthogonal Decomposition

2007 ◽  
Author(s):  
Timothy C. Allison ◽  
A. Keith Miller ◽  
Daniel J. Inman
Keyword(s):  
Finite Element ◽  
System Identification ◽  
Predictive Models ◽  
Structural Response ◽  
Orthogonal Decomposition ◽  
Nonlinear Structures ◽  
Response Data ◽  
Linear And Nonlinear ◽  
Identification Techniques ◽  
Proper Orthogonal

The Proper Orthogonal Decomposition (POD) is a method that may be applied to linear and nonlinear structures for extracting important information from a measured structural response. The POD is often applied for model reduction of linear and nonlinear systems and recently in system identification. Although methods have previously been developed to identify reduced-order predictive models for simple linear and nonlinear structures using the POD of a measured structural response, the application of these methods has been limited to cases where the excitation is either an initial condition or an applied load but not a combination of the two. This paper presents a method for combining the POD-based identification techniques for strictly free or strictly forced systems to identify predictive models for a system when only mixed response data are available, i.e. response data resulting from initial conditions and loads that are applied together. This method extends the applicability of POD-based identification techniques to operational data acquired outside of a controlled laboratory setting. The method is applied to finite element models of simple linear and nonlinear beams and is shown to identify an accurate predictive model for each beam when compared with results obtained by the finite element method.

scholarly journals Choice of Measurement Locations of Nonlinear Structures Using Proper Orthogonal Modes and Effective Independence Distribution Vector

2014 ◽  
Vol 2014 ◽  
pp. 1-6 ◽  
Author(s):  
T. G. Ritto
Keyword(s):  
Experimental Data ◽  
Computational Model ◽  
Proper Orthogonal Decomposition ◽  
Orthogonal Decomposition ◽  
Nonlinear Structures ◽  
Nonlinear Structure ◽  
Proper Orthogonal Modes ◽  
Distribution Vector ◽  
Proper Orthogonal

This paper proposes a methodology to automatically choose the measurement locations of a nonlinear structure/equipment that needs to be monitored while operating. The response of the computational model (or experimental data) is used to construct the proper orthogonal modes applying the proper orthogonal decomposition (POD), and the effective independence distribution vector (EIDV) procedure is employed to eliminate, iteratively, locations that contribute less for the independence of the target proper orthogonal modes.

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