从噪声测量数据中识别柔性结构的物理参数

A. Ohsumi, Nobuhide Nakano
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引用次数: 10

摘要

我们将注意力集中在一个反问题上,用于识别受随机干扰的悬臂梁数学模型中的物理参数,如杨氏模量和空气和结构阻尼系数,使用以非破坏性方式测量其振动的动态噪声数据。首先,用包含随机扰动下未知参数的Euler-Bernoulli型偏微分方程和包含观测噪声的振动数据的测量方程来描述悬臂梁的数学模型。将随机动态数据识别问题分为求(模态)状态估计的估计问题和确定未知参数的最小二乘问题,然后交替使用两种算法递归确定未知参数。最后,为了验证所提算法的有效性,进行了仿真研究和实验。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Identification of physical parameters of a flexible structure from noisy measurement data
We focus our attention on an inverse problem for identifying physical parameters such as Young's modulus and air and structural damping coefficients in a mathematical model of cantilevered beams subject to random disturbance, using dynamic noisy data measured on their vibrations taken in a non-destructive manner. First, we describe mathematical models of the cantilevered beam by an Euler-Bernoulli type partial differential equation including unknown parameters subject to random disturbance and the measurement equation taking vibration data including the observation noise. The identification problem using random dynamic data is divided into an estimation problem obtaining the (modal) state estimate and a least-squares problem determining unknown parameters, and then the unknown parameters are determined recursively by using two algorithms alternately. Finally, in order to verify the efficacy of the proposed algorithm simulation studies and experiments are shown.
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