ZY(J)7 electrohydraulic turnout switch equipment has been widely used in high-speed railway, and accurate fault diagnosis is helpful to the daily maintenance of high-speed railway turnout. Taking the fault text data of ZY( J) 7 turnout as the research object, a fault diagnosis model for high-speed railway turnout was proposed, which combined LDA topic model with association rules classification technology. Firstly, this model adopted LDA topic model to extract the feature of ZY(J)7 turnout fault text data. Secondly, due to the unbalanced data of each fault type of turnout, the original association rule classification algorithm was introduced into the concept of class support to deal with unbalanced data, and finally the fault diagnosis of ZY(J)7 switch was realized. Through the experimental analysis of ZY(J)7 turnout fault text data of a railway bureau from 2017 to 2019, the experimental results indicate that the classification precision and recall rate of the proposed fault diagnosis method are 95. 08% and 90. 24% respectively, which not only guarantees the accuracy of the whole classification, but also gets better classification performance of minority class.