摘要
针对现有测试性建模方法对系统不确定信息描述及分析上的不足,提出了基于贝叶斯网络的测试性建模与分析方法。首先结合贝叶斯网络的基本理论,阐述了系统测试性模型的构成要素及建立流程,用相关性矩阵表示系统故障-测试之间的关联,用条件概率矩阵描述两者间的不确定信息;然后给出了测试性指标的具体分析过程和算法;最后通过实例验证了方法的有效性。
To solve the difficulty to describe and analyze uncertain information for the testability modeling of the existing methods,an approach was proposed to model and analyze system testability on the basis of bayesian networks.Firstly,combining the basic theory of bayesian networks,the elements and steps of testability modeling were introduced.The dependency matrix was applied to express the dependency relation between failure and test,and uncertain information was described by the conditional probability matrix.Then,the paper introduced the analysis process and algorithm of testability targets.Finally,an example proves that the method is effective.
出处
《中国测试》
CAS
2011年第5期90-93,共4页
China Measurement & Test
关键词
贝叶斯网络
测试性建模
测试性分析
不确定信息
bayesian networks
testability modeling
testability analysis
uncertain information