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针对多状态、多冗余复杂系统的预测维修问题,提出一种以系统可靠性为中心的预测维修设计方法。利用GO法建立了系统的可靠性分析模型,基于马尔可夫过程理论获得部件的可靠性参数随时间变化的状态转移方程,并给出了部件和系统动态可靠性的计算方法。综合部件退化度、维修成本、对系统可靠性的影响等因素提出维修优先数(MPN)的概念,以定量描述部件的维修重要性。以系统可靠性是否达标为准则设定维修时刻,以维修时刻部件的MPN为依据确定维修顺序,以维修的单位时间成本最小为目标优化维修范围和维修项目。最后以某捷联惯性导航系统(SINS)为例进行了算法验证,仿真结果表明该预测维修方法的设计是可行的、有效的。
Aiming at the problem of predictive maintenance of multi-state and multi-redundant complex systems, a predictive maintenance design method based on system reliability is proposed. The reliability analysis model of the system is established by using the GO method. The state transition equations of the reliability parameters of the components over time are obtained based on the Markov process theory, and the calculation methods for the dynamic reliability of the components and systems are given. The concept of maintenance priority number (MPN) is proposed based on factors such as the degree of degradation of components, the cost of repairs, and the impact on system reliability to quantitatively describe the importance of component maintenance. To determine whether the reliability of the system as a criterion for the maintenance of time to MPN maintenance time components to determine the order of maintenance to repair the minimum unit cost of time as the goal of optimizing the scope of maintenance and repair projects. Finally, an algorithm is validated by a strapdown inertial navigation system (SINS). The simulation results show that the design of this method is feasible and effective.