Complexity Analysis of Time-Frequency Features for Vibration Signals of Rolling Bearings Based on Local Frequency

被引:4
|
作者
Tang, Youfu [1 ]
Lin, Feng [1 ]
Zou, Qian [2 ]
机构
[1] Northeast Petr Univ, Sch Mech Sci & Engn, Daqing 163318, Peoples R China
[2] Res Inst Petr Explorat & Dev, Beijing 100083, Peoples R China
关键词
EMPIRICAL MODE DECOMPOSITION; INTELLIGENT FAULT-DIAGNOSIS; LEMPEL-ZIV COMPLEXITY; SEVERITY ASSESSMENT; MEAN DECOMPOSITION; WAVELET TRANSFORM; ELEMENT BEARINGS; ALGORITHM;
D O I
10.1155/2019/7190568
中图分类号
O42 [声学];
学科分类号
070206 ; 082403 ;
摘要
The multisource impact signal of rolling bearings often represents nonlinear and nonstationary characteristics, and quantitative description of the complexity of the signal with traditional spectrum analysis methods is difficult to be obtained. In this study, firstly, a novel concept of local frequency is defined to develop the limitation of traditional frequency. Then, an adaptive waveform decomposition method is proposed to extract the time-frequency features of nonstationary signals with multicomponents. Finally, the normalized Lempel-Ziv complexity method is applied to quantitatively measure the time-frequency features of vibration signals of rolling bearings. The results indicate that the time-frequency features extracted by the proposed method have clear physical meanings and can accurately distinguish the different fault states of rolling bearings. Furthermore, the normalized Lempel-Ziv complexity method can quantitatively measure the nonlinearity of the multisource impact signal. So, it supplies an effective basis for fault diagnosis of rolling bearings.
引用
收藏
页数:13
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