Fault diagnosis of rolling bearings based on variational mode decomposition and calculus enhanced energy operator

被引：0

作者：

Zhang D. ^{[1
]}

Feng Z.-P. ^{[1
]}

机构：

[1] School of Mechanical Engineering, University of Science and Technology Beijing, Beijing

来源：

Gongcheng Kexue Xuebao/Chinese Journal of Engineering | 2016年 / 38卷 / 09期

关键词：

Bearings; Energy operator; Fault diagnosis; Mode decomposition;

D O I：

10.13374/j.issn2095-9389.2016.09.019

中图分类号：

学科分类号：

摘要：

Aiming at the characteristics of rolling bearing fault vibration signals and considering the merits of variational mode decomposition in mono-component separation and calculus enhanced energy operator in transient impulse detection, this article introduces a new method termed fault diagnosis of rolling bearings based on variational mode decomposition and calculus enhanced energy operator. Firstly, the vibration signal is decomposed into several intrinsic mode functions by variational mode decomposition to reduce the noise interferences and to satisfy the mono-component requirement by energy operator. Then, the sensitive intrinsic mode function containing the main fault information about the bearing is selected by the proposed criterion. Finally, the impulses are strengthened using calculus enhanced energy operator, and the bearing fault is diagnosed by the time domain waveform and Fourier spectrum of the sensitive mono-component instantaneous energy. The analysis results show that the proposed method can effectively diagnose the rolling bearing faults. © All right reserved.

引用

页码：1327 / 1334

页数：7

共 16 条

[11]

Dragomiretskiy K., Zosso D., Variational mode decomposition, IEEE Trans Signal Process, 62, 3, (2014)

[12]

Huang N.E., Shen Z., Long S.R., A new view of nonlinear water waves: the Hilbert spectrum, Annu Rev Fluid Mech, 31, 1, (1999)

[13]

Wu Z.H., Huang N.E., Ensemble empirical mode decomposition: a noise assisted data analysis method, Adv Adapt Data Anal, 1, 1, (2009)

[14]

Rilling G., Flandrin P., On the influence of sampling on the empirical mode decomposition, Proceedings of IEEE Conference on Acoustics, Speech and Signal Processing, pp. 3-44, (2006)

[15]

Wang Y., Markert R., Xiang J., Et al., Research on variational mode decomposition and its application in detecting rub-impact fault of the rotor system, Mech Syst Signal Process, 60, (2015)

[16]

Zhao X.N., Feng Z.P., Fault diagnosis of rolling element bearing based on ensemble empirical mode decomposition and cross energy operator, Chin J Eng, 37, (2015)

← 1 2 →