Comprehensive fault evaluation on maglev train based on ensemble learning algorithm

In order to realize comprehensive fault evaluation on faults occurred in maglev train, aim at the difficulty in establishing the evaluation weight matrix and subjection matrix parameter, faint comprehensive evaluation method based on ensemble learning algorithm is proposed. First, the structure of the suspension system of maglev train is analyzed and a fault diagnosis model is built. Then ensemble learning is introduced to the train model with learning ability. At last, this method is applied to fault evaluation on maglev train suspension system. In comparison to single and integration classification method, the emulational results prove that the ensemble method works better on the problem, the advantage of the ensemble learning algorithm is manifested, and practice has proved that this method is competent for precision demand.