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Characterization of Dynamic Structures Using Parametric and Non-parametric System Identification Methods

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Date Issued:
2014
Abstract/Description:
The effects of soil-foundation-structure (SFS) interaction and extreme loading on structural behaviors are important issues instructural dynamics. System identification is an important technique to characterize linear and nonlinear dynamic structures.The identification methods are usually classified into the parametric and non-parametric approaches based on how to modeldynamic systems. The objective of this study is to characterize the dynamic behaviors of two realistic civil engineeringstructures in SFS configuration and subjected to impact loading by comparing different parametric and non-parametricidentification results. First, SFS building models were studied to investigate the effects of the foundation types on the structural behaviors underseismic excitation. Three foundation types were tested including the fixed, pile and box foundations on a hydraulic shaketable, and the dynamic responses of the SFS systems were measured with the instrumented sensing devices.Parametric modal analysis methods, including NExT-ERA, DSSI, and SSI, were studied as linear identification methodswhose governing equations were modeled based on linear equations of motion. NExT-ERA, DSSI, and SSI were used toanalyze earthquake-induced damage effects on the global behavior of the superstructures for different foundation types.MRFM was also studied to characterize the nonlinear behavior of the superstructure during the seismic events. MRFM is anonlinear non-parametric identification method which has advantages to characterized local nonlinear behaviors using theinterstory stiffness and damping phase diagrams. The major findings from the SFS study are: *The investigated modal analysis methods identified the linearized version of the model behavior. The change of globalstructural behavior induced by the seismic damage could be quantified through the modal parameter identification. Thefoundation types also affected the identification results due to different SFS interactions. The identification accuracy wasreduced as the nonlinear effects due to damage increased. *MRFM could characterize the nonlinear behavior of the interstory restoring forces. The localized damage could bequantified by measuring dissipated energy of each floor. The most severe damage in the superstructure was observed withthe fixed foundation. Second, the responses of a full-scale suspension bridge in a ship-bridge collision accident were analyzed to characterizethe dynamic properties of the bridge. Three parametric and non-parametric identification methods, NExT-ERA, PCA andICA were used to process the bridge response data to evaluate the performance of mode decomposition of these methodsfor traffic, no-traffic, and collision loading conditions. The PCA and ICA identification results were compared with those ofNExT-ERA method for different excitation, response types, system damping and sensor spatial resolution. The major findings from the ship-bridge collision study include: *PCA was able to characterize the mode shapes and modal coordinates for velocity and displacement responses. Theresults using the acceleration were less accurate. The inter-channel correlation and sensor spatial resolution had significanteffects on the mode decomposition accuracy. *ICA showed the lowest performance in this mode decomposition study. It was observed that the excitation type andsystem characteristics significantly affected the ICA accuracy.
Title: Characterization of Dynamic Structures Using Parametric and Non-parametric System Identification Methods.
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Name(s): Al Rumaithi, Ayad, Author
Yun, Hae-Bum, Committee Chair
Catbas, Necati, Committee Member
Mackie, Kevin, Committee Member
University of Central Florida, Degree Grantor
Type of Resource: text
Date Issued: 2014
Publisher: University of Central Florida
Language(s): English
Abstract/Description: The effects of soil-foundation-structure (SFS) interaction and extreme loading on structural behaviors are important issues instructural dynamics. System identification is an important technique to characterize linear and nonlinear dynamic structures.The identification methods are usually classified into the parametric and non-parametric approaches based on how to modeldynamic systems. The objective of this study is to characterize the dynamic behaviors of two realistic civil engineeringstructures in SFS configuration and subjected to impact loading by comparing different parametric and non-parametricidentification results. First, SFS building models were studied to investigate the effects of the foundation types on the structural behaviors underseismic excitation. Three foundation types were tested including the fixed, pile and box foundations on a hydraulic shaketable, and the dynamic responses of the SFS systems were measured with the instrumented sensing devices.Parametric modal analysis methods, including NExT-ERA, DSSI, and SSI, were studied as linear identification methodswhose governing equations were modeled based on linear equations of motion. NExT-ERA, DSSI, and SSI were used toanalyze earthquake-induced damage effects on the global behavior of the superstructures for different foundation types.MRFM was also studied to characterize the nonlinear behavior of the superstructure during the seismic events. MRFM is anonlinear non-parametric identification method which has advantages to characterized local nonlinear behaviors using theinterstory stiffness and damping phase diagrams. The major findings from the SFS study are: *The investigated modal analysis methods identified the linearized version of the model behavior. The change of globalstructural behavior induced by the seismic damage could be quantified through the modal parameter identification. Thefoundation types also affected the identification results due to different SFS interactions. The identification accuracy wasreduced as the nonlinear effects due to damage increased. *MRFM could characterize the nonlinear behavior of the interstory restoring forces. The localized damage could bequantified by measuring dissipated energy of each floor. The most severe damage in the superstructure was observed withthe fixed foundation. Second, the responses of a full-scale suspension bridge in a ship-bridge collision accident were analyzed to characterizethe dynamic properties of the bridge. Three parametric and non-parametric identification methods, NExT-ERA, PCA andICA were used to process the bridge response data to evaluate the performance of mode decomposition of these methodsfor traffic, no-traffic, and collision loading conditions. The PCA and ICA identification results were compared with those ofNExT-ERA method for different excitation, response types, system damping and sensor spatial resolution. The major findings from the ship-bridge collision study include: *PCA was able to characterize the mode shapes and modal coordinates for velocity and displacement responses. Theresults using the acceleration were less accurate. The inter-channel correlation and sensor spatial resolution had significanteffects on the mode decomposition accuracy. *ICA showed the lowest performance in this mode decomposition study. It was observed that the excitation type andsystem characteristics significantly affected the ICA accuracy.
Identifier: CFE0005567 (IID), ucf:50295 (fedora)
Note(s): 2014-08-01
M.S.
Engineering and Computer Science, Civil, Environmental and Construction Engineering
Masters
This record was generated from author submitted information.
Subject(s): System Identification -- Modal Analysis -- Blind Source Seperation
Persistent Link to This Record: http://purl.flvc.org/ucf/fd/CFE0005567
Restrictions on Access: campus 2016-02-15
Host Institution: UCF

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