Remaining useful life prediction of bearings with the unscented particle filter approach

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Journal of Vibration and Shock ›› 2018, Vol. 37 ›› Issue (24) : 208-213.

WEN Juan, GAO Hongli

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Abstract

As a critical issue of condition-based maintenance, accurate prognosis of systems can improve the safety, availability and efficiency as well as reducing the maintenance cost.There are two main parts in model-based prognosis methods: degradation modelling and state estimation.Recently, particle filter (PF) has been widely applied in this area.However, there is a particle degeneracy problem with using PF.A remaining useful life (RUL) prediction approach of bearings was introduced by combining a stochastic process model and unscented particle filter (UPF) in this paper.Specifically, the degradation process of bearings was described with the stochastic process model, and the health state and model parameters were updated with UPF.Real test data were involved to demonstrate the effectiveness of the proposed technique.Compared with PF, the proposed method shows its superiority in particle degeneracy problem reduction and bearing RUL prediction.

Key words

condition-based maintenance / Unscented Particle filter / bearing / remaining useful life prediction / stochastic process model

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WEN Juan, GAO Hongli. Remaining useful life prediction of bearings with the unscented particle filter approach[J]. Journal of Vibration and Shock, 2018, 37(24): 208-213

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