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.