Research On Residual Life Prediction And Non - Perfect Maintenance Strategy Of Degraded System

In Recent years, PHM attracted more and more researchers’ attentions and shows it’s great power. Prognostics, which is the basis of PHM, is the focus of our research.In this thesis, the author introduces the stochastic filtering method which is used to estimate the remaining useful lifetime of a degradation system at first. Then the author studies how to estimate the parameters of stochastic filtering. Particularly, a new method to estimate the parameters in cases where there is no failure data is described by the author, which nobody has mentioned.At the same time, a model of the behavior of a degradation system is established, and imperfect maintenance is introduced into the framework. Then the stochastic filtering method can be modified for the effect of imperfect maintenance.Finaly, the author put forward a maintenance policy includes imperfect maintenance for a degradation system which is continuously monitored, which is based on the estimation of remaining useful lifetime. The author simulated the degradation, maintenance, estimation and decision making process. Then the optimal decision variables can got. Further more, the relationship between system paramertes and the optimal decision variables is studied, together with the performance.