In order to solve the problem of low accuracy of traditional algorithm for train number identification of railway freight trains, Faster R-CNN neural network for train number location of railway freight trains is proposed. The detailed features of the final convolution feature map are enhanced by adjusting the relevant size parameters and connection mode of the feature extraction network. The k-means ++ clustering algorithm is used to calculate the length width ratio of the train number area. The improved anchor size design makes the target detection frame more suitable for the actual train number area. In the experiment, data augmentation and dropout are used to improve the robustness of the network. The results show that the improved Faster R-CNN network has achieved 93. 15% accuracy in the location of railway freight train number, 90. 76% recall rate and 91. 94% comprehensive F1 index. It also shows that this method can accurately locate the railway freight train number and provide reliable data support for the identification process.