Wan Shuting, Zhang Xiong
Department of Mechanical Engineering, North China Electric Power University, Baoding 071003, China.
Entropy (Basel). 2018 May 21;20(5):388. doi: 10.3390/e20050388.
Kurtogram can adaptively select the resonant frequency band, and then the characteristic fault frequency can be obtained by analyzing the selected band. However, the kurtogram is easily affected by random impulses and noise. In recent years, improvements to kurtogram have been concentrated on two aspects: (a) the decomposition method of the frequency band; and (b) the selection index of the optimal frequency band. In this article, a new method called Teager Energy Entropy Ratio Gram (TEERgram) is proposed. The TEER algorithm takes the wavelet packet transform (WPT) as the signal frequency band decomposition method, which can adaptively segment the frequency band and control the noise. At the same time, Teager Energy Entropy Ratio (TEER) is proposed as a computing index for wavelet packet subbands. WPT has better decomposition properties than traditional finite impulse response (FIR) filtering and Fourier decomposition in the kurtogram algorithm. At the same time, TEER has better performance than the envelope spectrum or even the square envelope spectrum. Therefore, the TEERgram method can accurately identify the resonant frequency band under strong background noise. The effectiveness of the proposed method is verified by simulation and experimental analysis.
峭度图能够自适应地选择共振频带,然后通过分析所选频带来获得特征故障频率。然而,峭度图很容易受到随机脉冲和噪声的影响。近年来,对峭度图的改进主要集中在两个方面:(a)频带的分解方法;(b)最优频带的选择指标。在本文中,提出了一种名为Teager能量熵比图(TEERgram)的新方法。TEER算法采用小波包变换(WPT)作为信号频带分解方法,它可以自适应地分割频带并控制噪声。同时,提出了Teager能量熵比(TEER)作为小波包子带的计算指标。在峭度图算法中,WPT比传统的有限脉冲响应(FIR)滤波和傅里叶分解具有更好的分解特性。同时,TEER比包络谱甚至平方包络谱具有更好的性能。因此,TEERgram方法能够在强背景噪声下准确识别共振频带。通过仿真和实验分析验证了所提方法的有效性。