Parametric identification of structural nonlinearities from measured frequency response data


Arslan O., Aykan M., ÖZGÜVEN H. N.

MECHANICAL SYSTEMS AND SIGNAL PROCESSING, cilt.25, sa.4, ss.1112-1125, 2011 (SCI-Expanded) identifier identifier

  • Yayın Türü: Makale / Tam Makale
  • Cilt numarası: 25 Sayı: 4
  • Basım Tarihi: 2011
  • Doi Numarası: 10.1016/j.ymssp.2010.10.010
  • Dergi Adı: MECHANICAL SYSTEMS AND SIGNAL PROCESSING
  • Derginin Tarandığı İndeksler: Science Citation Index Expanded (SCI-EXPANDED), Scopus
  • Sayfa Sayıları: ss.1112-1125
  • Anahtar Kelimeler: Nonlinear structural dynamics, Nonlinear identification, Nonlinear modal model, Nonlinear modal analysis, Nonlinear modal testing, Experimental verification, SYSTEM IDENTIFICATION, DOMAIN
  • Orta Doğu Teknik Üniversitesi Adresli: Evet

Özet

Structural nonlinearity is a common phenomenon encountered in engineering structures under dynamic loading. In several cases, linear theory can suffice to analyze nonlinear systems to some extent. However, there are cases where nonlinear effects and therefore nonlinear analysis become unavoidable. In most of the engineering applications it is usually very difficult if not impossible to model nonlinearity theoretically, especially for nonlinear effects stemming from structural connections. Then it becomes necessary to detect, localize and parametrically identify nonlinear elements from measured vibration data. In this study, two different methods, one being a method suggested recently by two of the authors of this paper, and the other being again a method developed in an earlier work, are implemented on a test rig containing a nonlinear element. Both methods are capable of parametrically identifying nonlinearities from measured frequency response functions. It is aimed in this paper to asses the validity of each method by applying them to a real test structure and thus parametrically identifying the nonlinear element in the system to obtain a mathematical model, and then employing the model in harmonic response analysis of the system in order to compare predicted responses with measured ones. (C) 2010 Elsevier Ltd. All rights reserved.