Once the high-speed train is unstable, the operation safety of the train will be seriously threatened. Before the high-speed train appears to be unstable, it will enter a small hunting divergence state. Therefore, monitoring the train′s evolutionary trend of small hunting can predict the running status of trains. However, the existing literature rarely studies the evolution characteristics of small hunting, therefore, this paper proposes a high-speed train feature extraction framework based on EEMD-SVD-LTSA method, to identify whether the evolution trend is small divergence or small convergence, and then predict the train running status. The verification of online experimental data shows that the framework proposed in this paper can successfully extract the small convergence and small divergence operating characteristics of high-speed trains, and the recognition rate of using LSSVM can reach 100%, so as to predict the running status of high-speed trains in time and ensure the safety of trains.