Neural model of the dynamic behaviour of a non-linear mechanical system

被引:17
|
作者
Rouss, Vicky [1 ]
Charon, Willy [1 ]
Cirrincione, Giansalvo [2 ]
机构
[1] Univ Technol Belfort Montbeliard, M3M, F-90010 Belfort, France
[2] Politecn Torino, Dept Elect Engn, I-10129 Turin, Italy
关键词
Vibration; Neural network; Modelling; Non-linear mechanical system; Dynamics; NONPARAMETRIC IDENTIFICATION; LINEAR-SYSTEMS;
D O I
10.1016/j.ymssp.2008.09.004
中图分类号
TH [机械、仪表工业];
学科分类号
0802 ;
摘要
The availability of a model to prepare, supervise and analyse vibration tests of complex non-linear mechanical systems is vital. Analytical models, however, have some limitations when it comes to integrate the complex mathematical and physical parameters of non-linear mechanical systems. In this paper, an original approach based on multilayer perceptron neural network with a time regression input vector is proposed as an alternative solution. An experimental set is designed for this purpose: a non-linear mechanical system is subjected to random, shock and swept sine excitations on a vibrating platform. Its mechanical response is measured with accelerometers. The model is trained and validated based on the raw experimental data. Finally, simulation results from the analysis are presented and discussed. (C) 2008 Elsevier Ltd. All rights reserved.
引用
收藏
页码:1145 / 1159
页数:15
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