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Nonlinear Dynamic Identification of Beams Resting on Nonlinear Viscoelastic Foundations Based on the Time-Delayed Transfer Entropy and Improved Surrogate Data Algorithm

机译:基于时滞转移熵的非线性粘弹性基础围绕梁梁的非线性动态识别,改进代理数据算法

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摘要

In this work, the transfer entropy and surrogate data algorithm were introduced to identify the nonlinearity level of the system by using a numerical solution of nonlinear response of beams. A homogeneous Euler-Bernoulli beam was subjected to a time-varying concentrated load and resting on a nonlinear foundation. The Galerkin method was applied to discretize the dimensionless differential governing equation of the forced vibration, and then the fourth-order Runge-Kutta method was used to obtain the time-history response of the lateral displacement. In order to simulate different nonlinearity levels, different ratios between nonlinear parameters and linear parameters of foundation, as well as different Young’s moduli, were used. A nonlinearity index was proposed. In the case of different nonlinearity levels, the nonlinearity index was used to analyze the difference between the transfer entropy calculated from the original data and the transfer entropy calculated from the surrogate data. By comparing and analyzing the nonlinearity index values under different ratios, it was found that the nonlinearity index values generally increased with the increase of the ratio and the sum of nonlinearity index values had a positive correlation with the ratio. By comparing the nonlinearity index values of the transfer entropy results of beams with different Young's moduli, it was found that the sum of the nonlinearity index values generally decreased with the increase of Young's modulus. The numerical results demonstrate that the present approach could effectively quantify the nonlinearity in the response of a beam resting on a nonlinear foundation.
机译:在这项工作中,引入了转移熵和代理数据算法来识别系统的非线性水平,通过使用光束的非线性响应的数值解。将均匀的Euler-Bernoulli光束进行时变的浓缩载荷并在非线性基础上搁置。施加Galerkin方法以使强制振动的无量纲差分控制方程分开,然后使用四阶跑搏器方法来获得横向位移的时间历史响应。为了模拟不同的非线性水平,使用非线性参数与基础线性参数之间的不同比率,以及不同的杨氏模数。提出了非线性指数。在不同的非线性水平的情况下,非线性指数用于分析由原始数据计算的转移熵与由代理数据计算的转移熵之间的差异。通过比较和分析不同比率下的非线性指数值,发现非线性指数值通常随着比率的增加而增加,并且非线性指数值的总和与比率的正相关。通过比较与不同杨氏模数的梁的转移熵结果的非线性指数值,发现非线性指数值的总和通常随着杨氏模量的增加而降低。数值结果表明,本方法可以有效地量化在非线性基础上休息的梁的响应中的非线性。

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