Abstract
Bearing is an important component of a rotating machine; however, under normal operating conditions, it is subjected to fatigue which results in a defect called spalling. This work presents a monitoring fatigue of a thrust ball bearing on a bearing fatigue test bench. Spalling is artificially initiated on a bearing raceway. Vibration analysis is the method used to characterize the defect. The experimental procedure used is to monitor the operation of the ball bearing to the degradation with an online acquisition of the vibration readings. These data allow plotting the curve of fatigue (mathematical model). In order to obtain more realistic curve, the spalling evolution of several thrust ball bearings is monitored, first, under different loads then at different rotation speeds under a constant load. It found that growth follows a spalling power law and the damage is characterized by the model parameters.
Key words: Predictive maintenance, bearing, vibration analysis, spalling, rolling fatigue.
