Search - complex wavelet packet transform

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[File Format] dual-tree DL : 0: 首先将非平稳的故障振动信号进行双树复小波包分解，得到不同频带的分量；然后对每个分量求其峭度值和相关系数并进行比较；最后选取峭度值和相关系数较大的分量进行软阈值降噪和双树复小波包重构，即可有效地消除振动信号中噪声的干扰，同时保留信号中的有效信息即实现了故障特征信息的提取。-In view of the above situation, a new fault diagnosis method is proposed based on dual-tree complex wavelet packet transform and threshold de-noising. Firstly, the non-stationary fault signal is decomposed into several different frequency band components through dual-tree complex wavelet packet decomposition. Secondly, Kurtosis and the cross-correlation coefficient of each component are obtained and compared. Due to the kurtosis reflecting the signal variations, if the kurtosis value is bigger, the degree of the change of signal is bigger too. The correlation coefficient can reflect the proximity between the component and the original signal at the same time, the correlation coefficient is bigger, the more similar with the original signal. Finally, the components that have a bigger value are chosen to be de-noised by a soft threshold and reconstructed by dual-tree complex wavelet packet transform. The noise interference was eliminated effectively, and the effective si
Date : 2025-12-26 Size : 1.11mb User : 侯蒙蒙
[File Format] energy-leakage--dual-tree DL : 0: 首先根据高斯白噪声频率充满整个频带的特性，通过双树复小波包变换对高斯白噪声进行分解，利用频带能量泄漏的定量分析方法，验证了双树复小波包变换具有较低的频带能量泄漏特性；其次利用双树复小波包变换逐层分解信号，对每层分解所得分量求其FFT谱的峭度，得到基于双树复小波包变换的谱峭度图，根据图中峭度最大的原则，可以自动准确的选择信号分解最佳层数和最佳分量；最后将基于双树复小波包变换的谱峭度图的故障诊断方法应用于实际工程中，对齿轮故障振动信号进行分析，选择最佳分解层数和分量后利用希尔伯特包络解调，有效准确地提取了故障特征信息，验证了方法的可行性和有效性-The parameters of a filter were determined by experience, and that has a great influence on the results of signal processing. The discrete wavelet packet transform has a larger energy leakage of frequency band, which obviously affected the results of the envelope demodulation. It is necessary to have a method with a lower energy leakage of the frequency band before envelope demodulation. The dual tree complex wavelet packet transform (DT-CWPT) was a new signal processing method that had many good qualities. Because the energy leakage of the frequency band was smaller when the signal was decomposed by a dual tree complex wavelet packet transform, the dual tree complex wavelet packet transform was used to extract the fault feature information in the field of fault diagnosis. In this paper, first, according to the characteristics of Gaussian white noise, whose frequency was full of the whole frequency band, Gaussian white noise was decomposed by a dual-tree complex wavel
Date : 2025-12-26 Size : 392kb User : 侯蒙蒙