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

5Citations
Citations of this article
6Readers
Mendeley users who have this article in their library.

This article is free to access.

Abstract

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.

References Powered by Scopus

The empirical mode decomposition and the Hubert spectrum for nonlinear and non-stationary time series analysis

22924Citations
5176Readers
Get full text

Orthonormal bases of compactly supported wavelets

6328Citations
680Readers
Get full text
Get full text

Cited by Powered by Scopus

This article is free to access.

This article is free to access.

Get full text

Register to see more suggestions

Mendeley helps you to discover research relevant for your work.

Already have an account?

Cite

CITATION STYLE

APA

Tang, Y., Lin, F., & Zou, Q. (2019). Complexity Analysis of Time-Frequency Features for Vibration Signals of Rolling Bearings Based on Local Frequency. Shock and Vibration, 2019. https://doi.org/10.1155/2019/7190568

Readers over time

‘19‘21‘2401234

Readers' Seniority

Tooltip

PhD / Post grad / Masters / Doc 2

67%

Professor / Associate Prof. 1

33%

Readers' Discipline

Tooltip

Energy 2

40%

Engineering 2

40%

Agricultural and Biological Sciences 1

20%

Save time finding and organizing research with Mendeley

Sign up for free
0