Remaining useful life prediction based on particle filtering for high-speed pump in load sensing electro-hydrostatic actuator

摘要

This paper focuses on the remaining useful life (RUL) prediction of the electro-hydrostatic actuator (EHA) high-speed pump, for which a mathematical model describing the slipper wear caused degradation is proposed. In order to improve the long-term prediction accuracy, the developed method involves the particle filtering algorithm with the state dynamic model and a measurement model to estimate the posterior probability density function for the degrading state at present time and future time. According to the failure threshold set in advance, the RUL can be obtained. The proposed model avoids making simplifying assumptions of linearity and Gaussian noise system, but provides a robust long-term prediction framework for the RUL estimation with the consideration of uncertainties. Simulation experiments and analysis have been performed to verify the effectiveness and accuracy of the proposed life prediction model.