可修K/N(G)系统可靠性指标的仿真算法研究

A Simulation Algorithm for Reliability Index of Repairable K/N(G) System

利用Monte Carlo随机抽样技术,采用面向事件和面向固定时间间隔的双推进机制,提出了基于事件模块的可修K/N(G)系统可靠性指标仿真算法,算法能有效解决非指数分布类情况下,考虑部件已工作时间和不同维修策略等因素影响时,解析方法难以处理的系统可靠性分析难题,并且算法能同时对系统可靠性的平均指标和瞬时指标进行分析,从而可为指导装备的使用与维修管理提供有力的依据。算法采取的双推进机制保证了算法的仿真效率,基于事件模块的设计思想保证了算法的可扩展性,而且,经与解析算法比较,验证了仿真算法的正确性。

A simulation algorithm for reliability index of repairable K out of N system is offered based on Monte Carlo simulation method. The simulation clock in the algorithm is pushed by both event and fixed interval. The algorithm is modularized according to event. The algorithm can solve effectively the problem of reliability analysis when considering both worked time of components and diverse maintenance policy under non - exponential distribution, which is scarcely possible by using analytical method. The algorithm can analyze the average and instantaneous index simultaneously. The result of reliability evaluation can instruct the operation and maintenance of equipment. The high efficiency is guaranteed by double push rule and the good expansibility is guaranteed by modularized design idea. Furthermore, the validity of the simulation algorithm is validated by comparing with analytical method.