| 摘要: |
| 对作同步故障截尾与时间截尾的K个独立相同的幂律过程,即可靠性增长幂律模型,在无信息先验分布下给出了过程参数、当前的系统MTBF(平均故障间隔时间)与故障强度的Bayes点估计与区间估计,并将之与经典方法进行了比较,可避免非随机化最优置信下限的保守性和随机化最优置信下限的随机性。最后用两台发动机的数值例说明了这些方法。 |
| 关键词: 发动机故障 故障安全设计 可靠性增长 可靠性计算 |
| DOI： |
| 分类号:V430 |
| 基金项目:国家自然科学基金资助项目! ( 69774 0 3 4) |
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| Bayesian inferance on AMSAA BISE model and in application to engine |
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Zhou Yuanquan1, Guo Jianying2
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1.Beijing Inst of Structure and Environment,Beijing 100076,China;2.Harbin Univ of Science and Technology, Harbin 150080,China
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| Abstract: |
| Taking the noninformative prior distribution the Bayesian point and interval estimations for the parameters current system MTBF and failure intensity of synchronous time and failure truncated of K ,independent,identical power law process,i e AMSAA BISE model were presented The comparison of the Bayesian results and the classical results was given And these methods were illustrated with reliability calculation of two engines |
| Key words: Engine failure Fail safety design Reliability growth Reliability calculation |
