基于小波变换的工作模态参数识别方法研究

发布时间：2018-07-01 17:15

本文选题：工作模态参数识别 + 小波变换　；参考：《太原理工大学》2011年硕士论文

【摘要】：目前,基于振动的模态分析越来越受到科研机构和企业单位的重视,而模态参数识别又是其中最重要、最基础的一部分。由于实测的振动信号更能够真实的反应结构本身的固有特性和边界条件,因此工作模态参数识别就成为了模态参数识别新的研究和发展方向。基于以上原因,本文主要对工作模态参数识别的小波分析方法进行了探索性研究,在该方法的研究过程中,主要做了以下工作： (1)论文系统地总结了近年来基于工作模态参数辨识方法的大量文献,对其研究意义、国内外现状和一些模态识别方法进行了研究,并给了较为全面的论述,确定了论文研究的内容。 (2)论文从工作模态参数识别的角度出发,对小波分析的基本理论进行整理、归纳和阐述。对小波时频局部化的特点进行了理论推导,分析了小波时、频分辨率的关系。在满足参数辨识条件的基础上根据小波选取原则分析比.较了几种小波的各种特性参数,确定了选择Morlet小波作为系统模态参数识别的母小波。 (3)论文对小波变换的脊线提取方法进行了深入的研究,为建立模态参数识别的小波辨识方法奠定了基础。本文在平稳相位理论的基础上,建立了小波脊线提取的基本方法。通过对多种脊线提取方法的比较,选择了蚁群算法作为小波变换脊线提取的方法。仿真验证表明,蚁群算法不仅能够很好的提取小波变换的脊线,同时具有很高的抗噪性。 (4)论文建立了基于小波变换的工作模态参数识别方法。通过一个三自由度系统的仿真算例,验证了小波变换法识别模态的参数的可行性,通过与理论计算值比较验证了小波变换法识别模态参数的精度。 (5)论文通过随机白噪声激励下的悬臂梁来仿照它工作状态下的振动,分别通过小波变换、Polymax、ITD、ARMA模型时间序列等方法对悬臂梁进行了模态参数识别。同时对小波变换、Polymax、ITD、ARMA模型时间序列分析法识别的结果做了比较,证明了工作模态参数识别的小波变换方法要优于其他的几种辨识方法。
[Abstract]:At present, modal analysis based on vibration is paid more and more attention by scientific research institutions and enterprises, and modal parameter identification is the most important and basic part of it. Because the measured vibration signals can be more true to the inherent characteristics and boundary conditions of the structure itself, the working modal parameter identification has become a new research and development direction of modal parameter identification. Based on the above reasons, this paper mainly studies the wavelet analysis method of working modal parameter identification. The main works are as follows: (1) this paper systematically summarizes a large number of literatures based on working modal parameter identification in recent years, and studies its research significance, domestic and foreign current situation and some modal identification methods. And give a more comprehensive discussion, determine the content of the paper. (2) from the point of view of the identification of working modal parameters, the basic theory of wavelet analysis is sorted out, summarized and elaborated. The characteristics of wavelet time-frequency localization are theoretically deduced and the relationship between wavelet time-frequency resolution and wavelet time-frequency resolution is analyzed. On the basis of satisfying the condition of parameter identification, the ratio is analyzed according to the principle of wavelet selection. Compared with the various characteristic parameters of several kinds of wavelets, we select Morlet wavelet as the mother wavelet to identify the modal parameters of the system. (3) in this paper, the ridge extraction method of wavelet transform is studied deeply. It lays a foundation for establishing wavelet identification method for modal parameter identification. On the basis of stationary phase theory, the basic method of wavelet ridge extraction is established in this paper. Ant colony algorithm is chosen as the method of ridge extraction based on wavelet transform. Simulation results show that the ant colony algorithm not only can extract the ridge of wavelet transform, but also has a high noise resistance. (4) the method of working modal parameter identification based on wavelet transform is established in this paper. The feasibility of identifying modal parameters by wavelet transform is verified by a simulation example of a three-degree-of-freedom system. The accuracy of the wavelet transform method in identifying modal parameters is verified by comparing with the theoretical results. (5) the vibration of the cantilever beam excited by random white noise is simulated in this paper. The modal parameters of the cantilever beam are identified by using the time series of the Polymax ITD ARMA model of wavelet transform. At the same time, the results of the time series analysis of the wavelet transform Polymaxax ITDU ARMA model are compared, and it is proved that the wavelet transform method of working modal parameter identification is superior to other identification methods.
【学位授予单位】：太原理工大学
【学位级别】：硕士
【学位授予年份】：2011
【分类号】：TH165.3

【参考文献】