基于小波去噪算法和自调整迭代的频谱均衡方法

Zhi-Ming Chen, Zhongliang Luo, Tong Liu
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引用次数: 0

摘要

频谱均衡是随机振动控制的关键问题。提出了一种小波谱均衡方法。采用多分辨率变换方法,将频谱分解为分数阶标度信号,经过均衡化和去噪后重建用于频谱估计。提出了一种基于FFT和IFFT的改进小波变换算法,以消除分解和重构过程中的频率冗余。为了解决均衡化过程中收敛速度与精度之间的矛盾,提出了一种可变遗忘因子自调整迭代算法,并进行了收敛性分析。仿真结果表明,与传统的WOSA方法相比,该方法可以获得更好的均衡性能,并在抑制频谱振荡和保护频谱不连续之间取得平衡。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Spectrum equalization method based on wavelet denoising algorithm and self-adjusting iteration
Spectrum equalization is a key problem of random vibration control. A wavelet spectrum equalization method is proposed in this paper. With multi-resolution transform method, the spectrum is decomposed into fractional scaling signals, after equalization and denoising, they are reconstructed for spectrum estimation. An improved wavelet transform algorithm with FFT and IFFT is introduced to remove the frequency redundance during the decomposition and reconstruction. In order to resolve the contradiction between convergence speed and accuracy during equalization, a self-adjusting iteration algorithm with variable forgetting factor is proposed, the convergence analysis is also carried out. Simulation results show that comparing to traditional WOSA method, the proposed method can achieve better equalization performance, also provides a balance between spectrum oscillation suppression and spectrum discontinuity protection.
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