๐”– Bobbio Scriptorium
โœฆ   LIBER   โœฆ

NON-LINEAR MECHANICAL SYSTEMS IDENTIFICATION USING LINEAR SYSTEMS WITH RANDOM PARAMETERS

โœ Scribed by S. BELLIZZI; M. DEFILIPPI


Publisher
Elsevier Science
Year
2003
Tongue
English
Weight
233 KB
Volume
17
Category
Article
ISSN
0888-3270

No coin nor oath required. For personal study only.

โœฆ Synopsis


A method to identify the parameters involved in the non-linear terms of randomly excited mechanical systems is presented. It is based on the minimisation of an index function which reflects the difference between an analytical approximation of the powerspectral density function response and the measured one. Using the concept of non-linear modes, an equivalent linear system with random parameters is used to approximate the power-spectral density. The method is applied to the ECL benchmark.


๐Ÿ“œ SIMILAR VOLUMES


Identification of weakly non-linear syst
โœ H.J. Rice ๐Ÿ“‚ Article ๐Ÿ“… 1995 ๐Ÿ› Elsevier Science ๐ŸŒ English โš– 463 KB

Many vibrating systems when experimentally tested show weak non-linearity. In these cases linear response features such as natural frequencies and damping ratios though clearly identifiable, nevertheless show amplitude dependency. This paper describes an approach where the underlying non-linear diff

LINEAR PATH IDENTIFICATION OF GENERAL NO
โœ H.J. Rice; K.Q. Xu ๐Ÿ“‚ Article ๐Ÿ“… 1996 ๐Ÿ› Elsevier Science ๐ŸŒ English โš– 437 KB

A robust identification technique is presented which extracts the linear frequency response kernel from an input/response measurement of a general non-linear system. Also the number and significance of higher order frequency response kernels required for a complete identification may be assessed fro

NON-LINEAR SYSTEM IDENTIFICATION USING L
โœ YIMIN FAN; C. JAMES LI ๐Ÿ“‚ Article ๐Ÿ“… 2002 ๐Ÿ› Elsevier Science ๐ŸŒ English โš– 320 KB

This paper describes a new methodology to identify multi-degree-of-freedom non-linear systems from the system's operating data. The methodology includes a new non-linear model architecture which embeds feedforward neural networks to represent unknown nonlinearities in a lumped parameter model, and a

IDENTIFICATION OF LINEAR MECHANICAL SYST
โœ A. Fasana; B.A.D. Piombo ๐Ÿ“‚ Article ๐Ÿ“… 1997 ๐Ÿ› Elsevier Science ๐ŸŒ English โš– 343 KB

This paper describes how the impulse response function of a linear and time invariant dynamic system can be computed numerically by deconvolution techniques, starting from its input and output time histories. The integral equation governing the problem is transformed into a severely ill-conditioned

MODAL IDENTIFICATION OF WEAKLY NON-LINEA
โœ C. Soize; O. Le Fur ๐Ÿ“‚ Article ๐Ÿ“… 1997 ๐Ÿ› Elsevier Science ๐ŸŒ English โš– 438 KB

It is known that an efficient approach for modal identification of a weakly non-linear multidimensional second-order dynamical system consists of using a model based on equivalent stochastic linearisation with constant coefficients. Such a model leads to a good identification of the total power of t