中文摘要：

为了准确地提取滚动轴承损伤特征频率,提出一种基于频率切片小波变换的时频峭度谱分析方法。采用频率切片小波变换对振动信号进行时频分解,求取与各个频率分量对应的幅值峭度,由幅值峭度序列构造信号的时频峭度谱。以时频峭度谱的若干个较大谱峰对应的频率作为中心频率,确定相应的共振频带,并在时频空间选择时频切片,然后采用重构分离出这些信号分量,并用包络解调获取重构信号的包络。在此基础上,通过包络信号的等效功率谱确定滚动轴承的损伤特征频率。试验证明,这种方法可以有效地提取滚动轴承的特征频率,由于采用了多个频带保证了足够多的信号能量可用于包络分析,当轴承存在多种损伤时,也可以有效地鉴别不同损伤特征频率。

英文摘要：

In order to find defect characteristic frequencies of ball bearing accurately and effectively, a new time-frequency kurtosis spectrum analysis method is proposed based on the frequency slice wavelet transform（FSWT）. Firstly, Vibration signal of a monitored ball bearing is decomposed in time-frequency domain by applying the FSWT. Then, on the basis of the time-frequency decomposition result, a kind of kurtosis is calculated which is related to the amplitude of each frequency component in the time-frequency domain of the signal. By using the kurtosis sequence, a time-frequency kurtosis spectrum is obtained. Thereafter, several higher peaks on the spectrum curve are selected, frequencies related to these peaks on the spectrum are thought as the center frequencies of those resonance bands to be analyzed, and the analyzed resonance bands are also fixed yet at the same time. And then, according with the analyzed bands, the corresponding time-frequency slices are settled on the time-frequency decomposition plane of the signal. Afterwards, the components over these time-frequency slices are rebuilt by means of doing the reverse transform of the FSWT. To get envelops of these components, the demodulation processing is used. Finally, an equivalent power spectrum of these envelopes is established for discovering the defect characteristic frequencies of the monitored bearing. It is proved that the proposed method is able to extract the defect characteristic frequencies efficiently. In addition, because several frequency-bands are used, this makes enough energies of the signal to be used for performing the envelope analysis, when a ball bearing has several different kinds of defects it can identify the defect characteristic frequencies perfectly.