When the traditional image processing method detects the wear area on the tread of the wheel, due to the influence of the shadow and stains on the surface of the wheel, it is easy to cause misidentification. Ways to identify areas of wear. First, use a CCD camera to collect the low-speed wheel tread profile map, and then calibrate the worn area in the profile map to make labels, and use FCN-32S, FCN-16S, FCN-8S models for training. The experimental results show that the FCN-32S, FCN-16S, and FCN-8S models can effectively detect areas with large wear, and the FCN-8S model is significantly better than FCN-32S and FCN-16S for detecting point wear areas. , And there is no misrecognition phenomenon for the three models of the area with stain interference set in the experiment. Finally, the detection effect of FCN-32S, FCN-16S, and FCN-8S is evaluated by the MIoU value, and the number of model training is changed, the MIoU value will eventually stay near 0.7, and the detection effect is good.