首页> 外文期刊>Reliability Engineering & System Safety >Dependability estimation for non-Markov consecutive-k-out-of-n: F repairable systems by fast simulation
【24h】

Dependability estimation for non-Markov consecutive-k-out-of-n: F repairable systems by fast simulation

机译:非马尔可夫连续k出n:F可修复系统的可靠性估计

获取原文
获取原文并翻译 | 示例
       

摘要

A model of consecutive-k-out-of-n: F repairable system with non-exponential repair time distribution and (k-1)-step Markov dependence is introduced in this paper along with algorithms of three Monte Carlo methods, i.e. importance sampling, conditional expectation estimation and combination of the two methods, to estimate dependability of the non-Markov model including reliability, transient unavailability, MTTF, and MTBF. A numerical example is presented to demonstrate the efficiencies of above methods. The results show that combinational method has the highest efficiency for estimation of unreliability and unavailability, while conditional expectation estimation is the most efficient method for estimation of MTTF and MTBF. Conditional expectation estimation seems to have overall higher speedups in estimating dependability of such systems.
机译:本文介绍了一种具有非指数修复时间分布且具有(k-1)步马尔可夫依赖性的n可连续F可修复系统模型,以及三种重要的蒙特卡洛方法的算法,条件期望估计和两种方法的组合,以估计非马尔可夫模型的可靠性,包括可靠性,瞬态不可用性,MTTF和MTBF。数值例子表明了上述方法的有效性。结果表明,组合方法对不可靠性和不可用性的估计效率最高,而条件期望估计是对MTTF和MTBF估计的最有效方法。在估计此类系统的可靠性时,条件期望估计似乎总体上具有更高的提速。

著录项

相似文献

  • 外文文献
  • 中文文献
  • 专利
获取原文

客服邮箱:kefu@zhangqiaokeyan.com

京公网安备:11010802029741号 ICP备案号:京ICP备15016152号-6 六维联合信息科技 (北京) 有限公司©版权所有
  • 客服微信

  • 服务号