Reliability analysis and remaining useful life estimation of a two-variable phased degradation system

On the one hand, due to changes in the operating conditions or working environment of the equipment, the degradation process often exhibits characteristics of two-phase or even multi-phase. In contrast to single-phase degradation models, two-phase degradation modeling necessitates considering the variability of the change points and analyzing the characteristics of the degraded state at the change points. On the other hand, as sensor technology advances, multi-sensor data collection systems have become increasingly widespread, and combining data from several sources can considerably improve the accuracy of remaining useful life (RUL) estimation. However, the current research fails to simultaneously incorporate both of the aforementioned conditions. Consequently, constructing a multivariate phased deterioration model and estimating the RUL still present a significant challenge. With this particular consideration, this paper constructs a two-variable phased degradation model based on the Wiener process. The RUL analytic expression is derived by taking into account the diversity of individuals and the random nature of change points. A novel approach is provided to achieve precise detection of change points. The proposed model’s validity is ultimately confirmed through the use of a simulation dataset as well as two real working datasets.