Paper Title:
Non-Parametric Identification of Structural Nonlinearity with Limited Input and Output Measurements
  Abstract

In this paper, a technique is proposed for non-parametric identification of structural nonlinearity with limited input and output measurements. The identification algorithm is based on the classical Kalman estimator for the displacement and the velocity responses and the recursive least square estimation for the unmeasured excitation and the restoring force. Two different models are used to simulate nonlinear structures: One is a 4-storey shear-frame structure with excitation on the top floor and the nonlinearity occurs at the bottom floor. The other is also a 4-storey shear-frame structure with both excitation and the nonlinearity at the top floor. Two numerical examples are carried out for the two kinds of models. Bouc-Wen hysteretic models are used to simulate the nonlinear impact. The simulation results demonstrate the efficiency of the proposed technique with limited output measurements.

  Info
Periodical
Advanced Materials Research (Volumes 243-249)
Edited by
Chaohe Chen, Yong Huang and Guangfan Li
Pages
5403-5407
DOI
10.4028/www.scientific.net/AMR.243-249.5403
Citation
Y. Lei, Y. Wu, "Non-Parametric Identification of Structural Nonlinearity with Limited Input and Output Measurements", Advanced Materials Research, Vols. 243-249, pp. 5403-5407, 2011
Online since
May 2011
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$32.00
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