ADAPTIVE PROGNOSTICS FOR ROLLING ELEMENT BEARING CONDITION

Rolling element bearing failure is one of the foremost causes of breakdown in rotating machinery. This paper proposes a remaining life adaptation methodology based on mechanistic modeling and parameter tuning. Vibration measurement is used to estimate defect severity by monitoring the signals generated from rotating bearings. Through a defect propagation model and defect diagnostic model, an adaptive algorithm is developed to fine tune the parameters involved in the propagation model by comparing predicted and measured defect sizes. In this manner, the instantaneous rate of defect propagation can be captured despite defect growth behavior variation. Therefore, a precise estimation of the remaining life can be determined. Simulations and experimental results are presented to illustrate the implementation principles and to verify the applicability of the adaptive prognostic methodology.