BEARING CONDITION DIAGNOSTICS VIA VIBRATION AND ACOUSTIC EMISSION MEASUREMENTS

Abstract This paper investigates defect detection methods for rolling element bearings through sensor signature analysis, specifically the use of a new signal processing combination of the high-frequency resonance technique and adaptive line enhancer. Two transducers, the accelerometer and the acoustic emission sensor, are used to acquire data for this analysis. Experimental results are obtained for inner race and outer race defects. Results show the potential effectiveness of the signal processing technique to determine both the severity and location of a defect.