谐波分量提取对振动结构模态参数的影响

D. Mironovs, A. Mironov, A. Chate
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引用次数: 0

摘要

根据模态参数与力学性能的关系,通过监测它们的模态参数(频率、形状和阻尼)随时间的变化,可以估计静力结构(如桥梁和建筑物)的状态。运行模态分析(OMA)提供模态参数的估计。OMA的基本假设是激励力是随机的,其振幅和频率性质与白噪声相似。对于具有周期性动力激励的结构,如风力涡轮机或直升机叶片,则违背了这一假设,这使得oma的应用变得复杂和不可靠。在模态参数估计之前提取周期分量是一个挑战,否则会污染信号并掩盖模态信息。本文考虑了一种信号处理工具,用于从信号中提取周期分量,以执行OMA和估计模态参数。该工具是基于时间同步平均和利用转速表信号。通过比较信号处理技术对模态参数的影响,研究了信号处理技术对模态参数的影响。本文还考虑了该工具的有效性,并讨论了其可能的用途。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Harmonic components extraction influence on resulting modal parameters of vibrating structures
It is possible to estimate condition of static structures, like bridges and buildings, by monitoring how their modal parameters (frequency, shape and damping) change in time, based on modal parameters relation to mechanical properties. Operational modal analysis (OMA) provides estimation of modal parameters. OMA basic assumption is that excitation forces are random and their amplitude and frequency nature is similar to white noise. For structures with periodic dynamic excitation, like wind turbines or helicopter blades, this assumption is violated, which makes OMA application complicated and unreliable. There is a challenge of extracting periodic components before modal parameter estimation, which otherwise contaminate signals and mask modal information. This paper considers a signal processing tool for extraction of periodic components from signals aiming to perform OMA and to estimate modal parameters. The tool is based on time synchronous averaging and utilizes tachometer signals. The influence of signal processing technique on modal parameters is studied by comparing these parameters with and without given signal processing tool. The paper also considers the effectiveness of the tool and discusses its possible uses.
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