Reliability Modeling And Optimization Of Non-exponential Phased Mission System

With the developing of modern science and technology,the aerospace equipment grows more and more complex.Most of these aerospace systems are phased mission systems(PMSs).The whole lifetime of the PMSs can be divided into several time durations according to the different system configurations and functions at different time,like the satellites or the spacecraft.Compared the traditional single-phased system,the reliability modelling of the PMS is more complex due to the consideration of the dependency among phases while the system reliability can be assessed more accurately.Nowadays,with the development of the aerospace industry,the reliability research of the PMS has become an emerging research topic.But in the existing research of the PMS modelling and optimization methods,there exists one critical problem.Most of the researches assume that the failure time of the components follow the exponential distributions,so that the system dynamic behaviors can be solved with the Markov chains,but this assumption is not practical.So this dissertation is focused on the modelling and optimization methods of PMS consisting of non-exponential components.The research contributions and innovative outcomes are summarized as follows:(1)Reliability analysis of phased mission system with non-exponential and partially repairable componentsIn practice,many real PMSs,like the satellites,consist of mechanical components or mechatronics whose lifetime follow non-exponential distributions like the Weibull distribution.In this type of system,the Markov process is not capable of modeling the system dynamic behaviors.In this paper,the Semi-Markov Process(SMP)is applied to solve the problem that the components' lifetime in dynamic systems follows nonexponential distributions.And the modular method is applied to simplify the system model.A numerical approximation algorithm for the SMP is proposed to assess the reliability of the PMSs consisting of non-exponential components.Furthermore,the accuracy and calculation efficiency of the approximation algorithm are explored compared to the Monte Carlo simulation method.(2)Reliability analysis of phased mission system under random shocksMany PMSs,like the satellite or the spacecraft,work in the outer space for a long time.And the energetic charged particle and heavy particle within the randomly occurred cosmic rays have a significant impact on the electronics.These random shocks could lead to the degradation of components,even failure.In this paper,A Markov regenerative process(MRGP)based method is proposed to modelling the PMS under random shocks.Firstly,different shocks models for components are analyzed.Then,the components shocks models are integrated into the system MRGP model.At last,the PMSs under random shocks are analyzed along with the modular method and numerical method.And a sensitivity analysis is also provided for completion(3)Reliability assessment of multi-state phased mission system with non-repairable multi-state componentsIn practical,many systems with multistate components cannot be repaired,such as satellites or the spacecraft working in the outer space.To deal with complex dependency among phases,the phase algebra for multi-state components is proposed.Then,by applying the proposed phase algebra,the MMDD manipulation rules are improved into the phase dependency manipulation rules.Compared to the PMS-BDD model and traditional MMDD method,can do the system modelling process with less nodes and the self-conflicting paths can be automatically cancelled and the system MMDD model can be generated without additional steps.On the other hand,a Markov-renewal equation based method is proposed to deal with the non-exponential multistate components in the evaluation of the path probability.And by the iterative numerical algorithm,the system reliability is assessed by the proposed method and verified by comparing to the MC simulation method.(4)System optimization of phased mission system with mix redundancy strategy.A redundancy optimization method for the PMS with mix redundancy strategy.In the areospace industry,redundancy strategy is usually used to ensure the high reliability.In the existing researches of the PMS redundancy optimization research,only cold standby or the hot standby strategy is considered.In this paper,a mixed redundancy strategy,which is a general case of the hot standby and cold standby,is proposed to optimize the PMS.By applying the SMP and modular method,the optimization model of the PMS with mix redundancy strategy is established.And the component type,redundancy quantity and type of redundancy can be optimized at the same time by an improved genetic algorithm.