Fault diagnosis of rolling element bearing based on the empirical wavelet transform technique and correlation coefficient
H.A. Mattar, A., Sayed, H., K. Youne, Y., H. El-Mongy, H. (2023). Fault diagnosis of rolling element bearing based on the empirical wavelet transform technique and correlation coefficient. EKB Journal Management System, 180(0), 147-160. doi: 10.21608/erj.2023.330260
Abdelgawad H.A. Mattar; Hussien Sayed; Younes K. Youne; Heba H. El-Mongy. "Fault diagnosis of rolling element bearing based on the empirical wavelet transform technique and correlation coefficient". EKB Journal Management System, 180, 0, 2023, 147-160. doi: 10.21608/erj.2023.330260
H.A. Mattar, A., Sayed, H., K. Youne, Y., H. El-Mongy, H. (2023). 'Fault diagnosis of rolling element bearing based on the empirical wavelet transform technique and correlation coefficient', EKB Journal Management System, 180(0), pp. 147-160. doi: 10.21608/erj.2023.330260
H.A. Mattar, A., Sayed, H., K. Youne, Y., H. El-Mongy, H. Fault diagnosis of rolling element bearing based on the empirical wavelet transform technique and correlation coefficient. EKB Journal Management System, 2023; 180(0): 147-160. doi: 10.21608/erj.2023.330260

Fault diagnosis of rolling element bearing based on the empirical wavelet transform technique and correlation coefficient

Engineering Research Journal
Volume 180, Issue 0, December 2023, Page 147-160  XML PDF (8.18 MB)
Document Type: Original Article
DOI: 10.21608/erj.2023.330260
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Authors
Abdelgawad H.A. Mattar* 1; Hussien Sayed1; Younes K. Youne1; Heba H. El-Mongy2
1Department of Mechanical Design, Faculty of Engineering- Mataria, Helwan University, Egypt
2Department of Mechanical Design, Faculty of Engineering- Mataria, Helwan University, Egypt Centre for Applied Dynamics Research, School of Engineering, University of Aberdeen, UK
Abstract
Several time-frequency analysis methods have been applied to the detection and diagnosis of rolling-element bearing faults. One such method is the empirical wavelet transform (EWT), which is used for signal analysis. This study combines the EWT method with the correlation coefficient to diagnose bearing faults using experimentally measured vibration signals. First, the empirical wavelet transform method is used to analyze the vibration signal and extract the amplitude modulated-frequency modulated (AM-FM) modes. Subsequently, the correlation coefficient is computed to identify significant components that indicate bearing faults. Finally, the envelope spectrum is generated for these significant components in order to extract the characteristic frequencies associated with bearing faults. The findings demonstrate the effectiveness of this novel approach in accurately identifying bearing fault characteristics.
Keywords
Rolling-element bearings; Fault diagnosis; Empirical wavelet transform; Correlation coefficient; Signal processing
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