航空学报 > 2009, Vol. 30 Issue (9): 1661-1665

基于故障率的测试性验证试验故障样本分配方案

李天梅,邱静,刘冠军   

  1. 国防科技大学 机电工程与自动化学院
  • 收稿日期:2008-07-11 修回日期:2008-09-20 出版日期:2009-09-25 发布日期:2009-09-25
  • 通讯作者: 李天梅

Allocation Plan of Failure Samples Based on Failure Rate in Testability

Li Tianmei, Qiu Jing, Liu Guanjun   

  1. College of Mechatronics Engineering and Automation, National University of Defense Technology
  • Received:2008-07-11 Revised:2008-09-20 Online:2009-09-25 Published:2009-09-25
  • Contact: Li Tianmei

摘要: 现有的分层抽样算法中故障率数据不准确是导致测试性验证试验结果不可信的一个原因。为解决这个问题,提出了利用验前信息和Monte Carlo仿真相结合的方法计算故障率。首先考虑故障率的随机特性和量级范围,用Gamma分布来拟合故障率的概率分布,根据上下限分位点确定了Gamma分布中的超参数。然后利用舍取抽样得到了大量的服从Gamma分布的随机数,求平均值作为实际系统的故障率值。以此故障率数据进行分层抽样,得到的故障样本分配方案更合理,试验结果更可信。

关键词: 测试性验证试验, 故障样本分配, 分层抽样, 故障率, Gamma分布, 蒙特卡罗方法

Abstract: Inaccuracies in the present proportionate stratified sampling algorithm based on fuzzy failure rate data is one main cause which makes the testability demonstration results untrustworthy. In order to solve the problem, a new allocation plan is formed which takes into consideration the empirical prior information combined with Monte Carlo simulation. First, the Gamma distribution is applied to fit failure rate data by considering the randomness and order of failure rate, and then, the parameters in Gamma distribution is calculated by limit fractiles. Quantities of random numbers following Gamma distribution are gained through limiting samples, and the mean value of the random numbers is applied to allocate the failure sample. Finally, a conclusion is drawn that the allocation plan based on the method proposed in this article is rational and the result of corresponding testability demonstration test is much more trustworthy.

Key words: testability demonstration tests, allocation of failure sample, stratified sampling, failure rate, Gamma distribution, Monte Carlo methods

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