Obstacles are an important factor affecting train operation safety.Due to little size, small obstacles can be ignored easily. To solve above problems, an automatic detection algorithm had been proposed based on convolutional neural network. Data augmentation was used in this algorithm to balance the sample size and then convolutional neural network is used to feature fusion, combining the location information and semantic information of small obstacles. The experimental results show that the algorithm mentioned has good detection effect on small obstacles.