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

Joint Authors

Tang, Youfu
Lin, Feng
Zou, Qian

Source

Shock and Vibration

Issue

Vol. 2019, Issue 2019 (31 Dec. 2019), pp.1-13, 13 p.

Publisher

Hindawi Publishing Corporation

Publication Date

2019-07-10

Country of Publication

Egypt

No. of Pages

13

Main Subjects

Civil Engineering

Abstract EN

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.

American Psychological Association (APA)

Tang, Youfu& Lin, Feng& Zou, Qian. 2019. Complexity Analysis of Time-Frequency Features for Vibration Signals of Rolling Bearings Based on Local Frequency. Shock and Vibration،Vol. 2019, no. 2019, pp.1-13.
https://search.emarefa.net/detail/BIM-1211493

Modern Language Association (MLA)

Tang, Youfu…[et al.]. Complexity Analysis of Time-Frequency Features for Vibration Signals of Rolling Bearings Based on Local Frequency. Shock and Vibration No. 2019 (2019), pp.1-13.
https://search.emarefa.net/detail/BIM-1211493

American Medical Association (AMA)

Tang, Youfu& Lin, Feng& Zou, Qian. Complexity Analysis of Time-Frequency Features for Vibration Signals of Rolling Bearings Based on Local Frequency. Shock and Vibration. 2019. Vol. 2019, no. 2019, pp.1-13.
https://search.emarefa.net/detail/BIM-1211493

Data Type

Journal Articles

Language

English

Notes

Includes bibliographical references

Record ID

BIM-1211493