Conditioned and Orthogonalised Reverse Path Nonlinear Methods on Multi-Degree-of-Freedom System

Practical engineering structures commonly display nonlinear dynamic response when damage is present in the system. Hence, the studies on nonlinear system identification have increased within these past few years. Current study is aimed on the structural identification of nonlinear systems based on the extraction of underlying linear frequency response function (FRF). The methods chosen to obtain the FRF are the Conditioned Reverse Path (CRP) and the Orthogonalised Reverse Path (ORP) method. The well-known frequency-domain CRP method has been recognised for its ability in solving nonlinear problems; detecting and quantifying nonlinearities in structures. In contrary, the ORP is a new algorithm developed in time-domain which gives simpler formulation for describing the underlying linear dynamics of nonlinear systems. Results show that the performance of the new ORP algorithm in handling nonlinearities is as good as the CRP method. The ability of ORP method has become the aim of the current study to assess the robustness of both algorithms towards nonlinear system identification of structures with multi-degree-of-freedom (MDOF) system.

[1]  Winson Taam,et al.  Nonlinear System Analysis and Identification From Random Data , 1991 .

[2]  Martin Magnevall,et al.  Nonlinear structural identification by the “Reverse Path” spectral method , 2012 .

[3]  Gaëtan Kerschen,et al.  Generation of Accurate Finite Element Models of Nonlinear Systems – Application to an Aeroplane-Like Structure , 2005 .

[4]  L. Garibaldi.  APPLICATION OF THE CONDITIONED REVERSE PATH METHOD , 2003 .

[5]  Henry J. Rice,et al.  A procedure for the identification of linear and non-linear multi-degree-of-freedom systems , 1991 .

[6]  Pauziah Muhamad,et al.  On the orthogonalised reverse path method for nonlinear system identification , 2012 .

[7]  Rajendra Singh,et al.  IDENTIFICATION OF MULTI-DEGREE-OF-FREEDOM NON-LINEAR SYSTEMS UNDER RANDOM EXCITATIONS BY THE “REVERSE PATH” SPECTRAL METHOD , 1998 .

[8]  Walter Hoffmann,et al.  Iterative algorithms for Gram-Schmidt orthogonalization , 1989, Computing.

[9]  Charles R. Farrar,et al.  A review of nonlinear dynamics applications to structural health monitoring , 2008 .

[10]  D. Inman.  Nonlinearity in Structural Dynamics: Detection, Identification and Modelling , 2002 .

[11]  J. Bendat.  New techniques for nonlinear system analysis and identification from random data , 1990 .

[12]  Jonathan E. Cooper,et al.  Identification of multi-degree of freedom non-linear systems using an extended modal space model , 2009 .

[13]  Stefano Marchesiello.  APPLICATION OF THE CONDITIONED REVERSE PATH METHOD , 2003 .

[14]  Gaëtan Kerschen,et al.  Identification of a continuous structure with a geometrical non-linearity. Part I: Conditioned reverse path method , 2003 .

[15]  K. Worden,et al.  Past, present and future of nonlinear system identification in structural dynamics , 2006 .

[16]  Henry J. Rice,et al.  A generalised technique for spectral analysis of non-linear systems , 1988 .

[17]  Jean-Philippe Noël,et al.  Frequency-domain subspace identification for nonlinear mechanical systems , 2013 .