In this paper the solution of the multiclass classification problem of the events recognition during the movement of a bogie model along rails containing defects is described. Testing the layout of the rail condition monitoring system was described. The problem was solved using LSTM recurrent neural networks and implemented by Python programming language. The neural network was trained to classify three type of events used acceleration data. The method of the data collection and the description of the test stand is given. Conclusions about the efficiency of event recognition from a given set are made.