| مستخلص: |
Alumina grinding production process has the characteristics of complex production steps, strong coupling of each link, serious process lag, and large disturbances in the production process. Most of the alumina industry in China uses high-aluminum, high-silicon, low-iron, and insoluble diaspore as raw materials. Compared with the Bayer process that generally uses gibbsite as raw materials in foreign countries, the requirements for grinding are much higher. To better solve the alumina grinding production process, the controle requirements and information exchange requirements of each process must be optimized from the overall situation of the whole production process. This article mainly focuses on the research of optimization control in the front-end production process of alumina production, that is, the raw ore grinding link. Aiming at the problems of low production efficiency of the original system, frequent equipment failures, and many abnormal shutdowns, a set of optimized control system was constructed. The system optimizes the grinding process of the entire alumina production process by building an intelligent optimization platform for grinding, integrating data acquisition and analysis, optimizing control inference analysis, and implementing optimizing control. Under the premise of effectively ensuring the stable operation of the process and the qualified production quality indicators of each section, the working efficiency of the process is effectively improved, energy consumption is saved, and the number of operators and work intensity are reduced. [ABSTRACT FROM AUTHOR] |
