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An inverse decaying frequency modulation EMD method for closely spaced modal parameter identification in high precision with Laplace wavelet correlation filtering

机译:一种逆衰减频率调制EMD方法,高精度高精度的模态参数识别,LAPPACT小波相关滤波

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摘要

Modal parameter identification is a useful tool to reveal natural vibration characteristics in dynamic design and analysis. Due to the influence of closely spaced modes with close frequencies and large dampings, identification accuracy using traditional Hilbert-Huang transform is always unsatisfactory, since the deadline requirement of neighboring intrinsic mode functions cannot be satisfied when the frequency ratio (high frequency versus low frequency) of two adjacent modes is less than two. Therefore, an inverse decaying frequency modulation empirical mode decomposition method is proposed, in order to separate multiple closely spaced modes in high precision, which not only adjusts the frequency ratio by frequency modulation, but also decreases damping by inverse decaying simultaneously. Next, the modal parameters of each separated single mode are picked up by means of Laplace wavelet correlation filtering. The effectiveness of the proposed method is validated by simulated signals in noise and noise-free conditions, and compared with other methods, showing the advantages of high-precision, closely spaced mode identification. In addition, the proposed method is applied to the assembly tightness identification of bolts in an aero-engine rotor, which achieves successful results.
机译:模态参数识别是一种揭示动态设计和分析中的自然振动特性的有用工具。由于具有近距离频率和大型阻尼的紧密间隔模式的影响,使用传统的Hilbert-Huang变换的识别精度总是不令人满意的,因为当频率比(高频与低频)时不能满足相邻内在模式功能的截止日期要求两个相邻模式的小于两个。因此,提出了一种反衰减频率调制经验模式分解方法,以便以高精度分离多个紧密间隔模式,这不仅通过频率调制调节频率比,而且还通过同时衰减减少阻尼。接下来,通过拉普拉斯小波相关滤波拾取每个分离的单模的模态参数。通过噪声和无噪声条件的模拟信号验证所提出的方法的有效性,并与其他方法进行比较,显示出高精度,间隔的识别的优点。此外,所提出的方法应用于航空发动机转子中螺栓的组装密封性识别,这实现了成功的结果。

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