首页|基于ICEEMDAN和Hilbert包络谱的滚动轴承故障诊断研究

基于ICEEMDAN和Hilbert包络谱的滚动轴承故障诊断研究

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针对滚动轴承故障振动信号因属于非平稳特征信号而导致故障特征频率难以提取的问题,提出了基于改进自适应噪声完备集合经验模态分解(ICEEMDAN)和Hilbert包络谱的滚动轴承故障诊断方法.首先,利用ICEEM-DAN对故障信号进行模态分解,产生一系列的固有模态分量(IMF);然后,找出与原信号相关度较高的模态分量,作该模态分量的Hilbert包络谱图,并提取滚动轴承的故障特征频率.最终,通过对滚动轴承外圈和内圈的故障信号进行分析,并将结果与经验模态分解(EMD)的结果比较,证明了经过ICEEMDAN分解后Hilbert包络谱图能够明显反映轴承故障的特征频率,该方法可有效诊断滚动轴承的外圈和内圈故障.
Research on fault diagnosis of rolling bearing based on ICEEMDAN and Hilbert envelope spectrum
In addressing the challenge of extracting fault characteristic frequencies from non-stationary vi-bration signals in rolling bearings,a fault diagnosis method of rolling bearing was proposed based on Im-proved Complete Ensemble Empirical Mode Decomposition with Adaptive Noise(ICEEMDAN)and Hil-bert envelope spectrum method.First of all,the ICEEMDAN was used to decompose the fault signals into a series of Intrinsic Mode Function(IMF).Subsequently,the valid IMFs with high correlation to the orig-inal signal were extracted,and their corresponding Hilbert envelope spectrum was generated to extract the fault characteristics frequency of the rolling bearing.Through signal analysis of the outer and inner ring faults of rolling bearings and comparison with Empirical Mode Decomposition(EMD),it is demonstrated that the amplitude of the envelope spectrum after the decomposition based on the ICEEMDAN method can clearly reflect the characteristic frequency of bearing faults.The results affirm the effectiveness of this method in diagnosing the outer and inner ring faults of rolling bearings.

rolling bearingfault diagnosisICEEMDANHilbert envelope spectrum

张斌、程珩、孟倩

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山西工程职业学院机械工程系,山西太原 030009

太原理工大学机械与运载工程学院,山西太原 030024

滚动轴承 故障诊断 ICEEMDAN Hilbert包络谱

山西省高等学校科技创新项目

2022L709

2024

兰州理工大学学报
兰州理工大学

兰州理工大学学报

CSTPCD北大核心
影响因子:0.57
ISSN:1673-5196
年,卷(期):2024.50(3)
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