Review of research on ”Quality Optimization Control of Cement Vertical Grinding”

In view of the current situation of narrow cement particle size distribution and low efficiency in the vertical grinding process of new dry cement production process, the research and application dynamics of online cement quality detection, internal pressure difference optimization setting and modeling and control of the vertical grinding process of cement were analyzed, and the neural network algorithm was proposed to establish the vertical grinding process model of cement. The proportion integration differentiation (PID) control, fuzzy control, model predictive control and their combined control algorithms were summarized. In order to improve the grinding quality of cement vertical grinding powder, the feasibility of each method was analyzed. Finally, it is demonstrated that the proportional integral-generalized predictive control (PI-GPC) control method is used to achieve better control effect, which is conducive to solving the problem of narrow cement size distribution and improving cement quality.