Abstract: Track circuit fault log is an important data record in the daily operation and maintenance work on site.Aiming at the problem that the track circuit fault log is not fully utilized in the field work and the efficiency of manual analysis is low, a topic clustering analysis method of track circuit fault text based on spectral clustering algorithm was proposed.Firstly, the characteristics of track circuit fault text data were analyzed and text preprocessing was carried out, Word2vec model was used to train and obtain character-level vectors to realize the feature representation of track circuit fault text data in semantic space; Secondly, according to the spectral clustering characteristics of the Laplacian matrix, the high-dimensional fault text feature data clustering was converted into a spectral segmentation problem, for the three fault factors text data, the feature vectors of normalized Laplacian matrix were solved and a low dimensional fault text feature matrix was constructed, then the K-Means clustering algorithm was used to realize the fault text topic clustering analysis under three fault factors text data sets, and the hidden track circuit fault topic type and frequency information contained in the text data of different fault factors was obtained, and the visual analysis of the clustering results based on the t-distributed stochastic neighbor embedding algorithm was realized; Finally, comparative experiments were conducted on three fault factor text data sets using different clustering models.The experimental results show that the clustering model based on spectral clustering algorithm had better convergence performance while ensuring the clustering accuracy of fault text clustering; Based on the clustering visualization analysis results, it is verified that the different fault topic categories obtained have high semantic discrimination.Through this method, automated clustering mining and statistical analysis of track circuit fault text data can provide auxiliary support for on-site track circuit comprehensive maintenance and fault prevention.