Model-Based Adaptive Prognosis of a Hydraulic System

Fault diagnostic and prognostic methods are the extensive topics of condition-based maintenance system. These publications include a wide range of statistical approaches for model-based approaches. Uncertainty in prediction cannot be avoided; therefore, algorithms are working to help manage these uncertainties. Remaining useful lives (RUL) are regularly updated through adaptive degradation models identified by using the concept of sampling importance resampling (SIR) filter. The SIR filter algorithm has become a popular choice formodel-based progressive system. As a matter of study, we consider a hydraulic system and develop a detailed physics-based model and use extensive simulations to describe our prehistoric science approach and to evaluate its effectiveness and strength.