时频域滤波方法及其在颤振信号处理中的应用
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摘要
联合时频分析(JTFA)是研究非平稳信号的有效工具。如何在二维时频空间对信号进行滤波并重构一维时间序列是时频分析研究中的一个具有积极学术意义和明确应用价值的课题。本文在系统学习现有的各种时频分析及其综合算法的基础上,详细研究了时频域滤波的核心思想和基本方法,吸取了自适应时频分析和线性子空间投影Wigner-Ville变换的优点,提出了的两种新的时频域滤波方法,并通过理论分析和数字仿真完成了相应的数值特性与应用特性研究。
     根据颤振试验的原理和观测信号特点,本文将所提出的两种时频域滤波算法引入到了飞机结构亚临界响应分析的颤振边界预测(FBP)研究当中,给出了一种新的颤振边界预测方案,即通过联合时频分析与时频域滤波提取有效信号再进行模态参数提取与颤振边界预测。
     基于Matlab工程仿真平台和LabView虚拟仪器集成环境实现了数字仿真及实时分析软件的设计与开发。经数字仿真及在某型飞机全机气弹模型低速风洞颤振试验数据处理中的实际应用,取得了满意的效果。结果表明,本文方法在精度、有效性和数值特性等方面优于现有的时频域滤波方法,并具有较好的应用特性,可以满足工程应用的实际需求。
Joint time-frequency distributions represent the energy or intensity of signal simultaneously in time and frequency. It's a problem of great significance how to filtering a signal in joint time-frequency domain and reconstruct the time series from the time-frequency plane selected. In this thesis, the theory of joint time-frequency analysis and synthesis and time-frequency filtering is investigated. Two kinds of new time-frequency domain filtering methods are proposed based on adaptive decomposition and linear subspace projection. The theory analysis and method principle are presented The characteristics of the two methods are studied by computer numerical simulation. The results show that both the methods are reasonable and feasible.
    Focused on the features and requirements of flutter test data processing, the methods presented here are used to pickup the major information as a pre-processing technique The application scheme is brought out for flutter boundary prediction based on subcritica. turbulence response. The functions of the methods are investigated by computer simulation and further examined by using flutter testing data of low-speed wind-turne of some aeroelastical modes.
    The related software is developed on Matlab and Labview for Windows.
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