Title :
Bearing Faults Diagnosis Based on EMD and Wigner-Ville Distribution
Author :
Li, Hui ; Zhang, Yuping
Author_Institution :
Dept. of Electromech. Eng., Shijiazhuang Inst. of Railway Technol.
Abstract :
Wigner-Ville distribution (WVD) is a joint time-frequency analysis for non-stationary signals procession. The main difficulty with the WVD is its bilinear characteristic, which leads to cross terms in the time-frequency domain. Recently the technique of empirical mode decomposition (EMD) has been proposed as a novel tool for the analysis of nonlinear and non-stationary data. In this paper, key elements of the numerical procedure and principles of EMD are introduced. Wigner-Ville distribution based on EMD is applied in the research of the faults diagnosis of the bearing. Firstly, the original time series data is decomposed in intrinsic mode functions (IMFs) using the empirical mode decomposition. Then, the Wigner-Ville distribution for selected IMF is calculated. The experimental results show that Wigner-Ville distribution based on EMD not only successfully eliminate the cross terms but also effectively diagnosis the faults of the bearing
Keywords :
Wigner distribution; ball bearings; fault diagnosis; signal processing; time series; time-frequency analysis; Wigner-Ville distribution; bearing faults diagnosis; empirical mode decomposition; intrinsic mode functions; joint time-frequency analysis; nonstationary signals procession; signal processing; time series data; Fault diagnosis; Feature extraction; Fourier transforms; Low-frequency noise; Optical noise; Rail transportation; Railway engineering; Signal analysis; Signal processing; Time frequency analysis; Empirical mode decomposition; Faults Diagnosis; Signal processing; Time-frequency analysis; Wigner-Ville distribution;
Conference_Titel :
Intelligent Control and Automation, 2006. WCICA 2006. The Sixth World Congress on
Conference_Location :
Dalian
Print_ISBN :
1-4244-0332-4
DOI :
10.1109/WCICA.2006.1714113