Standby redundancy can meet system safety requirements in industries with high reliability standards. To evaluate reliability of standby systems, failure dependency among components has to be considered especially when systems have load-sharing characteristics. In this paper, a reliability analysis and state transfer scheduling optimization framework is proposed for the load-sharing 1-out-of-N: G system equipped with M warm standby components and subject to continuous degradation process. First, the system reliability function considering multiple dependent components is derived in a recursive way. Then, a Monte Carlo method is developed and the closed Newton-Cotes quadrature rule is invoked for the system reliability quantification. Besides, likelihood functions are constructed based on the measurement information to estimate the model parameters of both active and standby components, whose degradation paths are modeled by the step-wise drifted Wiener processes. Finally, the system state transfer scheduling is optimized by the genetic algorithm to maximize the system reliability at mission time. The proposed methodology and its effectiveness are illustrated through a case study referring to a simplified aircraft hydraulic system.

备用冗余可以满足具有高可靠性标准的行业中的系统安全要求。为了评估备用系统的可靠性，必须考虑组件之间的故障相关性，尤其是当系统具有负载共享特性时。本文针对装备了M的N：G负载分担系统提出了可靠性分析和状态转移调度优化框架。备用部件会变热，并且会不断降解。首先，以递归方式导出考虑多个相关组件的系统可靠性函数。然后，开发了蒙特卡洛方法，并调用了封闭的牛顿-考特斯正交规则进行系统可靠性量化。此外，基于测量信息构造似然函数，以估计活动和备用组件的模型参数，其退化路径通过逐步漂移的维纳过程建模。最后，通过遗传算法对系统状态转移调度进行了优化，以最大程度地提高任务时的系统可靠性。通过案例研究说明了所提出的方法及其有效性，该案例研究涉及简化的飞机液压系统。