Abstract: This paper focused on the problem of water seepage on the walls of traction substations, which could easily affect the normal operation of trains, and the low efficiency of manual inspection, studied a method for detecting water seepage on the walls. This method was designed based on the improved model combining MobileNetV2 network and DeeplabV3 network, used edge computing and 5G mobile communication technology for edge deployment. It was implemented accurate segmentation of the water seepage area on the wall of the traction substation, reduced the parameters of the model, and improved the accuracy of the model. PA (Pixel Accuracy) and MIoU (Mean Intersection over Union) indicators reach 98.82% and 95.32% respectively. The deployment plan is convenient and widely applicable, with a single frame execution time of only 40 ms under 2 T of computing power.