Parametric time-domain identification of multiple-input systems using decoupled output signals

Jian Li, Manuel Ruiz-Sandoval, Billie F. Spencer, Amr S. Elnashai

Research output: Contribution to journalArticle

4 Citations (Scopus)

Abstract

SUMMARY: Civil engineering structures are often subjected to multidirectional actions such as earthquake ground motion, which lead to complex structural responses. The contributions from the latter multidirectional actions to the response are highly coupled, leading to a MIMO system identification problem. Compared with single-input, multiple-output (SIMO) system identification, MIMO problems are more computationally complex and error prone. In this paper, a new system identification strategy is proposed for civil engineering structures with multiple inputs that induce strong coupling in the response. The proposed solution comprises converting the MIMO problem into separate SIMO problems, decoupling the outputs by extracting the contribution from the respective input signals to the outputs. To this end, a QR factorization-based decoupling method is employed, and its performance is examined. Three factors, which affect the accuracy of the decoupling result, including memory length, input correlation, and system damping, are investigated. Additionally, a system identification method that combines the autoregressive model with exogenous input (ARX) and the Eigensystem Realization Algorithm (ERA) is proposed. The associated extended modal amplitude coherence and modal phase collinearity are used to delineate the structural and noise modes in the fitted ARX model. The efficacy of the ARX-ERA method is then demonstrated through identification of the modal properties of a highway overcrossing bridge.

Original languageEnglish (US)
Pages (from-to)1307-1324
Number of pages18
JournalEarthquake Engineering and Structural Dynamics
Volume43
Issue number9
DOIs
StatePublished - Jul 25 2014

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civil engineering
Identification (control systems)
MIMO systems
identification method
structural response
Civil engineering
ground motion
damping
road
earthquake
Highway bridges
Factorization
Earthquakes
Damping
Data storage equipment
method

All Science Journal Classification (ASJC) codes

  • Geotechnical Engineering and Engineering Geology
  • Earth and Planetary Sciences (miscellaneous)

Cite this

Li, Jian ; Ruiz-Sandoval, Manuel ; Spencer, Billie F. ; Elnashai, Amr S. / Parametric time-domain identification of multiple-input systems using decoupled output signals. In: Earthquake Engineering and Structural Dynamics. 2014 ; Vol. 43, No. 9. pp. 1307-1324.
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Parametric time-domain identification of multiple-input systems using decoupled output signals. / Li, Jian; Ruiz-Sandoval, Manuel; Spencer, Billie F.; Elnashai, Amr S.

In: Earthquake Engineering and Structural Dynamics, Vol. 43, No. 9, 25.07.2014, p. 1307-1324.

Research output: Contribution to journalArticle

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AB - SUMMARY: Civil engineering structures are often subjected to multidirectional actions such as earthquake ground motion, which lead to complex structural responses. The contributions from the latter multidirectional actions to the response are highly coupled, leading to a MIMO system identification problem. Compared with single-input, multiple-output (SIMO) system identification, MIMO problems are more computationally complex and error prone. In this paper, a new system identification strategy is proposed for civil engineering structures with multiple inputs that induce strong coupling in the response. The proposed solution comprises converting the MIMO problem into separate SIMO problems, decoupling the outputs by extracting the contribution from the respective input signals to the outputs. To this end, a QR factorization-based decoupling method is employed, and its performance is examined. Three factors, which affect the accuracy of the decoupling result, including memory length, input correlation, and system damping, are investigated. Additionally, a system identification method that combines the autoregressive model with exogenous input (ARX) and the Eigensystem Realization Algorithm (ERA) is proposed. The associated extended modal amplitude coherence and modal phase collinearity are used to delineate the structural and noise modes in the fitted ARX model. The efficacy of the ARX-ERA method is then demonstrated through identification of the modal properties of a highway overcrossing bridge.

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