期刊
PROCEEDINGS OF THE INSTITUTION OF MECHANICAL ENGINEERS PART C-JOURNAL OF MECHANICAL ENGINEERING SCIENCE
卷 225, 期 C12, 页码 2831-2847出版社
SAGE PUBLICATIONS LTD
DOI: 10.1177/0954406211413215
关键词
Wigner-Ville distribution; cyclic spectral density; time-frequency analysis; non-stationary signals; rolling element bearing; fault diagnosis
资金
- National Natural Science Foundations of China [50875162, 51035007]
The vibration signals of rolling element bearings are random cyclostationary when they have faults. Also, statistical properties of the signals change periodically with time. The accurate analysis of time-varying signals is an essential pre-requisite for the fault diagnosis and hence safe operation of rolling element bearings. The Wigner distribution is probably most widely used among the Cohen's class in order to describe how the spectral content of a signal changes over time. However, the basic nature of such signals causes significant interfering cross-terms, which do not permit a straightforward interpretation of the energy distribution. To overcome this difficulty, the Wigner-Ville distribution (WVD) based on the cyclic spectral density (CSD) is discussed in this article. It is shown that the improved WVD, based on CSD of a long time series, can render the time-frequency distribution less susceptible to noise, and restrain the cross-terms in the time-frequency domain. Simulation and experiment of the rolling element-bearing fault diagnosis are performed, and the results indicate the validity of WVD based on CSD in time-frequency analysis for bearing fault detection.
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