| Abstract Scope |
Through in-depth research on the anode assembly process in the existing electrolytic aluminum production process, in order to improve the effective detection of the anode rod assembly and prevent unqualified products from entering the subsequent production process, AI intelligent detection technology is introduced. Through in-depth research on the actual application environment and supporting production data, the corresponding data model is established, multi-spectral technology is used to realize data collection, and the deep learning model of convolutional neural network is used to realize accurate identification of defects. AI intelligent identification and sorting technology is applied to the defect sorting of anode rod assembly. |