Bearing Fault Detection Using Acoustic Emission Signals Analyzed by Empirical Mode Decomposition

In condition monitoring of ball bearings, traditional techniques involving vibration, acceleration may not be able to detect a growing fault due to the low impact energy generated by the relative motion of the components. This study presents an experimental evaluation for incipient fault detection of lightly loaded ball bearings by using acoustic emission method. A table top bearing test rig is fabricated to simulate bearing faults such as inner race & outer race defect etc., with rotating shaft carrying low loads. The effectiveness of the acoustic analysis technique is demonstrated through signal processing techniques; use of Empirical Mode Decomposition (EMD) method to derive the characteristics features related to defective bearings from time domain and enveloped spectra in the frequency domain. The results reveal that the acoustic technique is more effective in detecting bearings’ failure than that of the vibration measurement.