自适应无参经验小波变换及其在转子故障诊断中的应用

摘要/Abstract

摘要： 为了实现经验小波变换中Fourier谱的自适应分割，提出了自适应无参经验小波变换(APEWT)方法。同时，为了克服希尔伯特变换解调的不足，更精确地估计信号的时频分布，提出了改进归一化希尔伯特变换(INHT)。通过分析仿真信号将APEWT和INHT方法与经验模态分解(EMD)、总体平均经验模态分解(EEMD)和局部特征尺度分解等方法进行对比，结果表明了APEWT和INHT方法的优越性。最后，将基于APEWT和INHT的时频分析方法应用于转子局部碰磨故障诊断，试验数据分析结果表明，所提出的方法不仅能够有效地诊断转子局部碰磨故障，而且诊断效果优于EMD和EEMD方法。

关键词: 转子故障, 碰磨, 经验模态分解, 希尔伯特变换

Abstract: To fulfill an adaptive separation of Fourier spectrum in EWT, an adaptive parameterless EWT(APEWT) method was proposed herein. To overcome the shortcomings of Hilbert transform and estimate more accurate time-frequency distribution of a given signal, an improved normalized Hilbert transform(INHT) was put forward. The proposed APEWT and INHT were compared with empirical mode decomposition(EMD), ensemble EMD(EEMD) and local characteristic-scale decomposition(LCD) methods and the analysis results demonstrate the effectiveness of the proposed method. Finally, APEWT and INHT based time-frequency analysis method were applied to local rubbing fault diagnosis of a rotor system, and the analysis results of experimental data indicate that the proposed method may fulfill rotor rubbing fault diagnosis effectively and have better effectiveness than that of EMD and EEMD methods.

Key words: rotor fault, rubbing, empirical mode decomposition, Hilbert transform

中图分类号:

郑近德, 潘海洋, 潘紫微, 罗洁思. 自适应无参经验小波变换及其在转子故障诊断中的应用[J]. 中国机械工程.

Zheng Jinde, Pan Haiyang, Pan Ziwei, Luo Jiesi. Adaptive Parameterless Empirical Wavelet Transform(EWT) and Its Applications to Fault Diagnosis of Rotor System[J]. China Mechanical Engineering.

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