Aiming at the problem of defect detection of circular screen printing pattern, an improved algorithm model based on yolov5 is used to detect the defect of printing pattern. In this experiment, the network structure of yolov5 model is changed according to the actual situation. Firstly, the backbone of yolov5 network is optimized and improved, and the attention mechanism module is introduced to extract the features of channel attention and spatial attention of input pictures respectively. Secondly, aiming at the small target of printing defects, the detection layer structure of the network is modified. The experimental results show that the accuracy of the improved yolov5 detection algorithm is improved by 14.4%, and the detection speed is also improved, reaching 43.1fps, which meets the requirements of real-time detection.