An aided decision method for aluminum electrolytic cells based on attention mechanism
In the process of aluminum electrolysis production,in order to maintain energy balance and material balance of the electrolytic cell,it is neces-sary to provide control parameters to the production system based on expert experience to ensure stable cell conditions.However,the historical production data of aluminum electrolysis cells have problems such as excessive accumulation and complex parameter correlation,and relying solely on expert experi-ence cannot accurately determine the aluminum electrolysis cells that require parameter adjustment.In response to the above issues,this paper designs an attention mechanism-based multi temporal auxiliary decision-making method for aluminum electrolysis cells:using spatial encoders instead of convolu-tional networks to extract local features,establishing a self attention encoder neural network multi temporal classification model,and integrating the histori-cal experience of some experts to improve the accuracy of the model in discriminating aluminum electrolysis cells.The results of the ablation experiment in-dicate that the spatial encoder module is superior to the CNN module;The experimental results on real production data of an aluminum smelter show that this method is superior to traditional methods such as expert experience and DTW,with practical value provided in decision-making of aluminum electrol-ysis production.
万方数据
维普
