摘要
提出了一种用于产品性能退化数据的统计模型和分析方法。研究了由于可观测环境过程影响引起退化的单一单元系统可靠性。仅用单元当前的工作环境观测量估计失效时间分布,单元的当前工作环境被表征为有限状态半马尔可夫过程(SMP)。为了利用马尔可夫特性,通过状态保留时间的观测量和转移率将环境状态逗留时间近似为位相型(PH)随机变量。PH分布的使用使得现有解析结论容易应用于遭受连续时间马尔可夫链形式变化环境过程的单元可靠性评估。利用陀螺仪性能退化分析作为实例阐明了提出方法的有效性,并与通过Monte Carlo仿真获得的结果进行了比较。
The reliability of a single-unit system experiencing degradation due to the influence of a general observable environment process is considered. In particular, the failure time distribution is evaluated using only observations of the unit＇s current operating environment which is characterized as a finite semi-Markov process （SMP）. In order to impose the Markov property, the generally distributed environment state sojourn times are approximated as phase-type （PH） random variables using observations of state holding times and transition rates. The use of PH distributions facilitates the use of existing analytical results for reliability evaluation of units subject to an environment process that evolves as a continuous-time Markov chain. The procedure is illustrated through a numerical example for performance degradation of gyroscopes, and the results are compared with those obtained via Monte Carlo simulation.
出处
《中国惯性技术学报》
EI
CSCD
北大核心
2010年第2期255-260,共6页
Journal of Chinese Inertial Technology
基金
国家自然科学基金资助项目(60736026)
国家教育部新世纪优秀人才支持计划项目(NCET-07-0144)
关键词
位相型近似
可靠性
退化
马尔可夫过程
phase-type approximation
reliability
degradation
Markov process
