Bearing Fault Feature Extraction Method Based on Variational Mode Decomposition of Fractional Fourier Transform

被引:2
|
作者
Wei, Ming Hui [1 ,2 ]
Jiang, Li Xia [1 ,2 ]
Zhang, Di [3 ]
Wang, Bin [4 ]
Tu, Feng Miao [1 ,2 ]
Jiang, Peng Bo [1 ,2 ]
机构
[1] Southwest Petr Univ, Sch Mechatron Engn, Chengdu 610500, Peoples R China
[2] Sichuan Univ, Oil & GAs Equipment Technol Sichuan Prov Sci & Te, Cengdu 610500, Peoples R China
[3] Civil Aviat Flight Acad China, Xinjin Branch, Chengdu 611430, Peoples R China
[4] 3-607 Chenhuili,Dagang St, Tianjin 300280, Peoples R China
基金
中国国家自然科学基金;
关键词
fractional Fourier transform; variational mode decomposition; feature extraction; Fault diagnosis;
D O I
10.1134/S1061830922030056
中图分类号
TB3 [工程材料学];
学科分类号
0805 ; 080502 ;
摘要
A new method of fault feature extraction based on the fractional fourier transform variational mode decomposition (FRFT-VMD) method is proposed. First, the core idea of this method is to perform the optimal fractional fourier transform (FRFT) on the original signal. And then the transformed signal is subjected to variational mode decomposition (VMD). Aiming at the problem that the order of FRFT is difficult to determine, a fourth-order central moment (FOCM) method is proposed to determine the optimal order. And use the kurtosis standard deviation criterion (KSDC) to optimize the parameters of VMD. So that FRFT-VMD can be optimized. Finally calculating the kurtosis and impulse factor of the decomposed signal, so as to realize the extraction of fault characteristics. The research results of experimental data show that the signals extracted by this method contain more and more obvious fault characteristic frequencies, which greatly improves the accuracy of fault diagnosis in different states of the bearing normal state, inner ring fault, ball body fault, outer ring fault, etc.
引用
收藏
页码:221 / 235
页数:15
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