摘要
针对目前测试性预计方法缺乏对不确定性全面考虑的现象,从测试和故障两个方面分析了测试性预计过程中的不确定性问题,基于贝叶斯网络测试性模型对不确定性测试问题进行了建模与分析,基于混合诊断模型对故障不确定性问题进行了建模与分析,并最终将贝叶斯网络测试性模型与混合诊断模型相融合,给出了一种兼容IEEE Std 1522的基于混合诊断贝叶斯网络模型的测试性指标预计方法,测试性指标预计结果的可信度明显提高。
In view of ignorance of uncertain problem existed in test and diagnosis, current testability prediction method tends to be inaccu-rate. The hybrid diagnostic Bayesian networks can model the uncertain relationship between tests and failure sources, failure modes and functions. In the paper, a method of hybrid diagnostic Bayesian networks was given based on uncertain testability modeling and prediction, which is compatible with IEEE Std 1522. The model of hybrid diagnostic Bayesian Networks is a kind of enhanced diagnostic inference model which can provide testability prediction solution with high accuracy.
出处
《弹箭与制导学报》
CSCD
北大核心
2013年第2期177-180,F0003,共5页
Journal of Projectiles,Rockets,Missiles and Guidance
关键词
贝叶斯网络
混合诊断模型
测试性
不确定性
预计
Bayesian networks
hybrid diagnostic model
testability
uncertainty
prediction
