基于复解析小波变换的包络分析遗传算法

Lianfeng Huang, Xiongpeng Wu, Caidan Zhao, Minghui Gao, Haiyan Xiong
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引用次数: 1

摘要

本文讨论了希尔伯特变换包络分析、谱图包络分析和复解析小波包络分析。针对希尔伯特变换易受噪声干扰、频谱分析受短时窗影响、Morlet小波参数靠经验手动设定等缺点,提出了一种基于遗传算法和复Morlet小波变换的改进算法。采用遗传算法对Morlet小波参数进行优化,无需经验,小波变换能有效消除随机噪声的影响。此外,实验结果表明,该改进算法优于其他算法。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Genetic algorithm based analysis of envelope using complex analytical wavelet transform
Hilbert transform envelope analysis, spectrogram envelope analysis, and complex analytical wavelet envelope analysis are discussed in this paper. According to the disadvantages such as Hilbert transform susceptible to noise interference, spectrum analysis affected by short-time window, and the parameters of Morlet wavelet set manually by experience, an improved algorithm based on genetic algorithm and complex Morlet wavelet transform is put forward in this paper. By genetic algorithm, the parameters of Morlet wavelet are optimized without experience, and the wavelet transform can effectively eliminate the influence caused by random noise. Moreover, the experimental results show that this improved algorithm outperforms the other algorithms.
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