Intelligent Optimization Control of Plate Plan View Pattern Based on Intermediate Slab Pattern Vision Inspection and BWO-DNN Algorithm

In the production process of plate, the main factors affecting the yield of plate are the crop cutting and edge losses It is very important to accurately predict the crop pattern of plates and effectively control the plan view pattern. In this paper, a detection scheme is proposed to obtain plan view pattern of intermediate slab and finished plate by placing the detection devices after roughing mill and finishing mill respectively. The image processing algorithm is used to obtain the dataset of plan view pattern parameters, and the plan view pattern prediction and control model of plate is established based on BWO-DNN algorithm. The BWO algorithm is used to optimize the hyperparameters in DNN algorithm to complete the establishment of the intelligent model. In terms of model analysis, goodness of fit (R2) and mean absolute error (MAE) are used as evaluation indicators. The results show that the intelligence model established based on BWO-DNN has good predictive and control performance, realizing intelligent prediction of the crop pattern of plates and parameters optimization of plan view pattern control. The actual production verification on site shows that the irregular area of plate head and tail can be reduced by 17.2 % and 22.6% respectively.