Research on S700K switch machine fault diagnosis based on fast Bayesian network

作者：Xiao Shuang Men · 发表于：Journal of Railway Science and Engineering · 年份：2015 · 被引用次数：2 · 研究领域：Rough Sets and Fuzzy Logic、Advanced Computational Techniques and Applications、Advanced Decision-Making Techniques

The impact of switch machine on the safety and efficiency of railway transportation is significant. A senior Bayesian network fault diagnosis method based on rough set theory was proposed according to the complex uncertainty relation between the fault reasons and phenomena. Firstly,the fault diagnosis decision table that used the improved discernibility matrix algorithm to eliminate attribute that had little effect on the result was formed to obtain the most simple fault diagnosis decision table. Secondly,the Bayesian network model was established according to the relationship between failure phenomenon and failure type,and the probability of kinds of failure was solved using reasoning algorithm. The algorithm could simplify Bayesian network structure and decrease calculation speed through reducing attribute. Finally,the correctness of the intelligent fault diagnosis method was verified through a case example of a service section switch machine fault.