Nonlinear identifications using transmissibility: Dynamic characterisation of Anti Vibration Mounts (AVMs) with standard approach and nonlinear analysis

被引:11
|
作者
Carrella, A. [1 ]
机构
[1] Univ Bristol, Fac Engn, Bristol BS8 1TR, Avon, England
关键词
Nonlinear identification; Transmissibility measurement; Amplitude-dependent stiffness; Anti vibration mounts; ISOLATOR;
D O I
10.1016/j.ijmecsci.2012.06.014
中图分类号
TH [机械、仪表工业];
学科分类号
0802 ;
摘要
Anti Vibration Mounts (AVMs) are very common passive vibration isolation devices used in a variety of engineering applications. These are, in most cases, off-the-shelf items which engineers select on the basis of the manufacturer's specifications (in particular the dynamic stiffness). However, only seldom the nominal values of the stiffness of AVMs (especially that of elastomeric mounts) are close to those measured. It can be argued that the main reason for the disagreement is the nonlinear characteristic of the mounts. In practice, the difference between nominal and measured stiffness value can cause major problems to engineers. In fact, in many engineering applications, structures are required to be tested for clearance or certification purposes (e.g. hardware items on helicopters): if an AVM has been selected on the basis of its nominal stiffness its choice may present problems when these are excited at high amplitude of vibration, when the nonlinear behaviour becomes pronounced. In this paper an existing identification method based on Frequency Response Function (FRF) data is shown to be applicable also when transmissibility is measured. Transmissibility is a frequency-dependent, non-dimensional, function which is particularly useful especially when the test item is excited at the base. In this article, the applicability of the method is first demonstrated using numerical simulations. Subsequently, it is shown that the method allows extraction of amplitude-dependent stiffness characteristics of the mount from standard dynamic tests. This enables calculation of stiffness functions and building of a more refined numerical model of the system. The advanced model is used to predict the system's response which compares well with measured data. (c) 2012 Elsevier Ltd. All rights reserved.
引用
收藏
页码:74 / 85
页数:12
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