Modal Analysis and Identification of Structural Non-Linearity,

Abstract

When it is suspected that a structure is non-linear, e.g. unfamiliar distortions of transfer functions, unacceptable deviations in curve fits or significant amplitude dependent behaviour is observed, there are few, if any, established methods for reliably identifying the nature or quantifying the importance of non-linearity. The reasons for wanting to pursue an analysis into the non-linear domain whereby a reliable identification method would be of value can be described in three general ways. Firstly, an accurate linear model of the system is desired if possible. This may be the case where a comparison is to be drawn with the results from a linear finite element analysis. Secondly, the existence of non-linearity is to established and the need is for an estimate of its effect on the structures response in service, i.e. the behaviour of the non-linear system is desired when the input is typical of operating conditions. Finally, it is required that the non-linearity be identified fully enough to enable an implicit mathematical model to be constructed, such as a set of non-linear differential equations. These may then be solved to predict the response of the structure to various input conditions whereby the dependence of the modal parameters on these can be established. In this case the non-linear coefficients of the structural system equations have to be determined.

Document Details

Document Type
Technical Report
Publication Date
Jan 01, 1984
Accession Number
ADP003683

Entities

People

  • G. R. Tomlinson
  • N. E. Kirk

Organizations

  • University of Victoria

Tags

DTIC Thesaurus Topics

  • Differential Equations
  • Equations
  • Finite Element Analysis
  • Identification
  • Linear Differential Equations
  • Linear Systems
  • Linearity
  • Mathematical Models
  • Modal Analysis
  • Models
  • Transfer Functions

Readers

  • Adaptive Control and Estimation with Uncertainty in Dynamic Systems.
  • Control Systems Engineering.
  • Educational Psychology