Research on DFT-Oriented Uncertain Dependency Model
System-level testability analysis and fault diagnosis have been largely based on a dependency model or a multi-signal model. But since these models are based on Boolean logic without concerning the uncertainty during a test, the performance of diagnosis and prognosis based on this model results in inaccuracy. To solve the problem, a method to identify and model the uncertainty was presented. Firstly, the conditional probabilities of true alarm and false alarm were treated as the measurement of uncertainty. Then the probabilities were estimated by means of Bayesian statistics approach. Based on those probabilities, an uncertain dependency model was established through higher-order dependency analysis. Finally, a mechatronics servo system was used to demonstrate the presented modeling method. The experimental results show that the uncertain dependency model lends naturally to real-world necessities such as reducing false alarm and improving diagnostic precision.
Design for testability dependency model higher-order dependency analysis uncertain reasoning
LIU Guan-jun YANG Peng QIU Jing
College of Mechatronics Engineering & Automation, National University of Defense Technology, Changsha, China, 410073
国际会议
北京
英文
2007-08-05（万方平台首次上网日期，不代表论文的发表时间）