Data-driven Modeling of Ball Mill Load and Cement Particle Size

Ball mill is the core equipment in the process of cement combined grinding. Load of ball mill is an important index to characterize the running state of ball mill. Cement particle size is a key index to determine the quality of cement products. In this paper, the load of ball mill and the particle size of cement are studied. In view of their strong coupling and uncertainty, it is difficult to establish mathematical models through mechanism analysis. A data-driven modeling method is proposed. According to the actual production data, the model of ball mill load and cement granularity is established by using recurrent neural network. The validity of the data driven model is verified by simulation analysis to identify the load of ball mill and the size of cement.