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Detection of nonlinear structural behavior using time-frequency and multivariate analysis

  • Prawin, J. (Academy of Scientific and Innovative Research, CSIR-Structural Engineering Research Centre, CSIR Campus) ;
  • Rao, A. Rama Mohan (Academy of Scientific and Innovative Research, CSIR-Structural Engineering Research Centre, CSIR Campus)
  • Received : 2018.03.22
  • Accepted : 2018.09.29
  • Published : 2018.12.25

Abstract

Most of the practical engineering structures exhibit nonlinearity due to nonlinear dynamic characteristics of structural joints, nonlinear boundary conditions and nonlinear material properties. Hence, it is highly desirable to detect and characterize the nonlinearity present in the system in order to assess the true behaviour of the structural system. Further, these identified nonlinear features can be effectively used for damage diagnosis during structural health monitoring. In this paper, we focus on the detection of the nonlinearity present in the system by confining our discussion to only a few selective time-frequency analysis and multivariate analysis based techniques. Both damage induced nonlinearity and inherent structural nonlinearity in healthy systems are considered. The strengths and weakness of various techniques for nonlinear detection are investigated through numerically simulated two different classes of nonlinear problems. These numerical results are complemented with the experimental data to demonstrate its suitability to the practical problems.

Keywords

nonlinear systems;wavelets;Hilbert-Huang transform;principal component analysis;Holder exponent;null subspace analysis

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