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Reliability assessment of multi-state phased mission system with non-repairable multi-state components

机译:具有不可修复的多状态组件的多状态分段任务系统的可靠性评估

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摘要

Phased mission systems (PMSs) like satellites and spacecraft perform their functions over non-overlapping mission periods, called phases. One of the challenges in assessing reliability of PMSs comes from considering thes-dependence among phases, and the consideration on the multi-state behavior of components and systems makes the reliability analysis even more difficult. To effectively address this problem, a multi-state multivalued decision diagram algorithm for PMS and a multi-state multi-valued decision diagram model for phased mission system (PMS-MMDD) method is developed for the reliability modelling of non-repairable multi-state components. Based on the Semi-Markov process, a Markov renewal equation-based method is developed to deal with non-exponential multi-state components and a numerical method, the trapezoidal integration method, is used to compute the complex integrals in the path probability evaluation. A case study of a multi-state attitude and orbit control system in a spacecraft is analyzed to illustrate the proposed PMS-MMDD model and the Markov renewal equation-based evaluation method. The accuracy and computation efficiency of the proposed method are verified by the Monte Carlo simulation method.
机译:像卫星和航天器这样的分相任务系统(PMS)在非重叠任务阶段(称为阶段)执行其功能。评估PMS可靠性的挑战之一是考虑各阶段之间的依赖性,而对组件和系统的多状态行为的考虑使可靠性分析更加困难。为了有效解决此问题,针对不可修复的多状态可靠性模型,开发了一种用于PMS的多状态多值决策图算法和用于相控任务系统的多状态多值决策图模型(PMS-MMDD)方法组件。在半马尔可夫过程的基础上,发展了一种基于马尔可夫更新方程的方法来处理非指数多状态分量,并采用数值方法梯形积分法来计算路径概率评估中的复杂积分。分析了航天器多状态姿态和轨道控制系统的案例,以说明所提出的PMS-MMDD模型和基于马尔可夫更新方程的评估方法。蒙特卡罗仿真方法验证了该方法的准确性和计算效率。

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