Remaining useful life prediction for equipment with periodic maintenance

Remaining useful life (RUL) is a key procedure of prognostics health management (PHM), which is central to guarantee the safety of the equipment. In general, some maintenance activities will be implemented during the operation of an industrial equipment. Thus, to describe the degradation of an actual equipment, the effect of these maintenance activities must be considered. However, the current literature still falls short in degradation modeling and RUL prediction for equipment with maintenance. In this paper, we proposed a Brownian motion-based degradation model with periodic negative jump, to describe the degradation process of an equipment with periodic maintenance. We use maximum likelihood estimation (MLE) method to identify the unknown parameters in the model. And the Monte Carlo method is used to obtain the numerical probability density function (PDF) of the RUL with a given failure threshold. Finally, a numerical simulation is presented to illustrate the effectiveness of the proposed method.