The steel industry is the supporting industry of social development. In order to improve the level of industrial automation and effectively detect the surface defects of steel plates, an improved YOLOv3(You Only Look Once) detection algorithm was proposed. Firstly, wavelet - median filter is used to improve the image contrast. Then, a scale output is added on the darknet-53 network to enhance the algorithm's ability to recognize small target defects. Finally, in order to enhance the accuracy of the algorithm model, the original loss function of the algorithm is optimized and the improved YOLOv3 algorithm model is obtained. The mAP value of the improved network on the test set is 7.9 higher than that of the original YOLOv3 network, which has a better application prospect in plate surface defect detection.