Experimental Validation of Pseudo Receptance Difference (PRD) Method for Nonlinear Model Updating

Canbaloglu G., ÖZGÜVEN H. N.

33rd IMAC Conference and Exposition on Structural Dynamics, Florida, United States Of America, 2 - 05 February 2015, pp.293-306 identifier identifier

  • Publication Type: Conference Paper / Full Text
  • Doi Number: 10.1007/978-3-319-15221-9_26
  • City: Florida
  • Country: United States Of America
  • Page Numbers: pp.293-306


In real life applications most of the structures have nonlinearities, which restrict us applying model updating techniques available for linear structures. Well-established FRF based model updating methods would easily be extended to a nonlinear system if the FRFs of the underlying linear system (linear FRFs) could be experimentally measured. When frictional type of nonlinearity co-exists with other types of nonlinearities, it is not possible to obtain linear FRFs experimentally by using low level forcing. Pseudo Receptance Difference (PRD) method, recently developed by the authors, calculates linear FRFs of a nonlinear structure by using FRFs measured at various forcing levels, and simultaneously identifies multiple nonlinearities in the system. Then any model updating method can be used to update the linear part of the mathematical model. In this present work, the PRD method is used to predict the linear FRFs from nonlinear FRFs, and the inverse eigensensitivity method is employed to update the linear finite element (FE) model of a nonlinear structure. A real nonlinear T-beam test structure is used to validate the accuracy of the proposed method. First, the linear FRFs are calculated from nonlinear FRFs measured at different forcing levels, and simultaneously, the nonlinearities in the structure are identified. Then the FE model of the linear part of the structure is updated. Finally, the accuracy of the updated nonlinear model of the test structure is demonstrated by comparing the calculated and measured FRFs of the test structure at several different forcing levels.