Physics of failure-based degradation modeling and lifetime prediction of the momentum wheel in a dynamic covariate environment

We consider the problem of reliability modeling and evaluation of the Momentum Wheel (MW) in long-life satellites under small sample circumstances, proposing a physics-of-failure-based degradation model and life prediction method for such MWs in a dynamic covariate environment. From the results of a physics of failure experiment, we first derive models for the distribution and microcirculation of bearing lubricant. Next, we identify the qualitative and quantitative relationships between the key factors, e.g. rotation speed and bearing temperature, and the loss of lubricant. Then, taking the bearing temperature as a dynamic covariate, we build a degradation model for lubricant loss in the bearing assembly that corresponds to a Wiener process with drift that is positively associated with the covariate. To estimate the parameters of this degradation model, we use the method of maximum likelihood and the data from the physics of failure experiment. To predict the lifetime of an individual MW under orbital conditions, we suggest using Empirical Mode Decomposition (EMD) and regression analysis to model the trend in bearing temperature derived from telemetry data. Bootstrap simulation provides a satisfactory way of coping with the various sources of uncertainty in our prediction. Based on the predicted bearing temperature and the lubricant loss model, we estimate the amount of lubricant lost by an individual MW bearing, and hence obtain the lifetime of the lubrication system by comparing the predicted values for residual lubricant with the designed lubricant capacity. A case study involving data from a particular type of MW demonstrates the merits of this lifetime prediction method that we propose.

► Lubricant distribution and microcirculation models in bearing assembly of MW.
► Negative exponential relation between lubricant loss and bearing temperature.
► Wiener process with bearing temperature as covariate for lubricant loss.
► EMD based method for in-orbit telemetric data processing.
► A case study that validates the proposed method.