机电工程技术2024，Vol.53Issue(2)：75-79,5.DOI:10.3969/j.issn.1009-9492.2024-00008
基于CEEMDAN和双重峭度准则的电动机轴承故障特征频率估计方法
A Fault Characteristic Frequency Estimation Method of Motor Bearing Based on CEEMDAN and Double Kurtosis Criterion
摘要
Abstract
Bearing fault signal collected by vibration sensor is easily polluted by strong noise,which degrades the accuracy of the fault characteristic frequency estimation.For this problem,a high accurate method of the bearing fault frequency estimation based on complete ensemble empirical mode decomposition with adaptive noise(CEEMDAN)and double kurtosis criterion is proposed.It is very challenging to select the appropriate components from alternative modes to reconstruct the fault characteristic signal after the signal decomposition.The distribution of the modal components corresponding to noise is closer to the normal distribution after the isotropic circle transformation(standard whitening treatment).Consequently,two kurtosis criterions are introduced.The first kurtosis criterion is to screen out suspected fault signals from the original modal components,and the second kurtosis criterion is to remove noise components by the isotropic circle transformation.Hence,the intersection modes of the double kurtosis criterion are used to reconstruct the bearing fault characteristic signal.Furthermore,the complex envelope method and FFT are used to obtain the envelope spectrum of the signal.In addition,the three-line spectrum correction method is employed to achieve more accurate fault characteristic frequency estimation.Compared with some existing methods,simulation experiments and measured bearing fault data of outer and inner rings show that the proposed method can obtain high accuracy estimates by a simple signal screening method.关键词
自适应噪声完备集合经验模态分解/轴承故障检测/峭度/故障诊断Key words
complete ensemble empirical mode decomposition with adaptive noise(CEEMDAN)/bearing fault detection/kurtosis/fault diagnosis分类
机械制造引用本文复制引用
解春维,申伟霖,余美仪..基于CEEMDAN和双重峭度准则的电动机轴承故障特征频率估计方法[J].机电工程技术,2024,53(2):75-79,5.基金项目
国家自然科学基金资助项目(61972092) （61972092）
