迭代奇异值方法在机械结构模态分离 重构中的应

Application of iterative singular value method in mode seperation and reconstruction of mechanical structure

  • 摘要: 通过时频分解技术,将复杂的多模态信号分解成单模态成分,从而可以采用比较简单可靠的单模态识别方法 对机械结构复杂模态信号进行参数辨识。经验小波变换(EWT)算法能有效解决模态分离问题,一些改进型 EWT 算法能有效克服噪声干扰,但是在模态重构时,滤波器彼此重叠、临近模态互相干扰,会不可避免地出现重构模态失 真。本文针对模态分离重构问题展开研究,分析了 EWT 算法在模态分离重构中面临的重构失真问题,提出了基于 迭代截断奇异值分解(ITSVD)方法的改进算法,并在仿真信号和含结合面机械结构模型振动响应信号上进行了应 用。结果表明,所提 ITSVD?EWT 算法能够更好地实现机械结构模态分离重构。

     

    Abstract: Complex multi?mode signals can be decomposed into single mode components using time?frequency decomposition tech? nology. This allows for the use of a simple and reliable single mode identification method to identify the complex modal signals of mechanical structure. Empirical wavelet transform (EWT) method can effectively decompose the modes, and some revised meth? ods even can overcome the strong noise. However, when reconstructing the modes, the reconstructed mode could be distorted due to overlapping filters and closely spaced components. Focusing on the problem of mode decomposition and reconstruction, this pa? per analyzes the problem of distorted reconstructed mode of EWT method, proposes a revised method based on the Iterative Trun? cated Singular Value Decomposition (ITSVD) method, and applies this new method to both the synthesis signal and the experimen? tal signal from the vibration response of a mechanical structure model with a joint surface. The results suggest that the proposed ITSVD?EWT method is more effective in mode decompose and reconstruction.

     

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