The invention discloses a multi-parameter intelligent threshold criterion of a high-speed train. Firstly, the working condition parameters and the state monitoring data of the high-speed train are collected, and the state monitoring data are divided according to the working condition parameters. Then, the fuzzy kernel clustering is used to analyze the condition monitoring data, and the center coordinates and the distance within the class are obtained. At last, the central coordinate, the distance within the class and the regression relationship between the multi-parameters of the working condition are calculated, and then the threshold value under various working conditions are intelligently calculated, and the high-speed train is intelligently alerted. The method is simple and applicableto the determination of intelligent threshold of monitoring data of high-speed trains under off-design conditions.