Early Fault Diagnosis of Gear Box based on Variational Mode Decomposition and Fast Spectral Kurtosis

Zhao Wei

doi:10.16578/j.issn.1004.2539.2018.01.030

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Early Fault Diagnosis of Gear Box based on Variational Mode Decomposition and Fast Spectral Kurtosis

更新时间：2022-10-20

- Early Fault Diagnosis of Gear Box based on Variational Mode Decomposition and Fast Spectral Kurtosis
- Vol. 42, Issue 1, Pages: 143-149(2018)
- 作者机构：
  
  1. 包头轻工职业技术学院自动化学院
- 作者简介：
- 基金信息：
- DOI：10.16578/j.issn.1004.2539.2018.01.030
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[1]赵玮.基于VMD和FSK的齿轮箱早期故障诊断[J].机械传动,2018,42(01):143-149.

Zhao Wei. Early Fault Diagnosis of Gear Box based on Variational Mode Decomposition and Fast Spectral Kurtosis. [J]. 42(1):143-149(2018)
[1]赵玮.基于VMD和FSK的齿轮箱早期故障诊断[J].机械传动,2018,42(01):143-149. DOI： 10.16578/j.issn.1004.2539.2018.01.030.

Zhao Wei. Early Fault Diagnosis of Gear Box based on Variational Mode Decomposition and Fast Spectral Kurtosis. [J]. 42(1):143-149(2018) DOI： 10.16578/j.issn.1004.2539.2018.01.030.

摘要

针对齿轮箱齿轮早期故障特征信号微弱且受环境噪声影响严重,故障特征频率难以提取以及传统共振解调方法中带通滤波器参数不易确定的问题,提出了基于变分模态分解（Variational Mode Decomposition,VMD）和快速谱峭度（Fast Spectral Kurtosis,FSK）的故障诊断方法。利用VMD对采集到的齿轮故障振动信号进行分解,得到一系列窄带本征模态分量（Band-limited Intrinsic Mode Functions,BLIMFS）;依据相关系数准则,选取与原始信号相关系数较大的分量进行快速谱峭度计算,用谱峭度图确定最佳的中心频率和带宽进行相应带通滤波处理。最后对滤波后的信号进行能量算子包络解调分析,即可从包络谱中准确地识别齿轮故障特征频率。通过仿真信号和齿轮故障实验数据对所提方法进行了验证,结果表明,该方法能够有效地降低噪声的影响,准确地提取齿轮早期故障信号中的微弱特征信息。

Abstract

Aiming at the gear fault early sign signal is weak and the noise influence is serious,it is difficult to extract the fault characteristic frequency and band-pass filter parameters are not easy to determine the problem,a fault diagnosis method is proposed based on the variational modal decomposition（VMD） and fast spectral kurtosis（FSK）. Firstly,the vibration signal of the bearing fault is decomposed by VMD to get a series of band-limited intrinsic mode functions（BLIMFS）. Then,according to the correlation coefficient criterion,the spectral kurtosis is calculated for the components with large correlation coefficient,and the best center frequency and bandwidth are determined by spectral kurtosis graph. Finally,the filtered signal is analyzed by the energy operator envelope demodulation. The fault characteristic frequency can be extracted accurately from the envelope spectrum. Through the analysis of simulation signal and experimental data of gear fault,the results show that the method can effectively reduce the influence of the noise and accurately realize the extraction of weak gear fault feature information.

关键词

变分模态分解快速谱峭度算法齿轮早期故障包络解调

Keywords

VMDFast spectral kurtosisGearEarly faultEnvelope demodulation

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