Caustic Ratio Of The Alumina Production Process And The Dissolution Rates Of Intelligent Integrated Predictive Model

Ratio of Soda to Aluminate (RSA) and Leaching Rate(LR) are two very important economical and technical indices in the process of High-Pressure Digestion (HPD) of alumina. Not only they affect output of alumina and alkali consumption, but also they make great influence on successive production of alumina. However, at present it is difficult to measure RSA and LR timely, which makes it hard to achieve real-time control of the whole process of production. Therefore, How to implement on-line measurement of RSA and LR by establishing prediction model using intelligent integrated modeling, is significant for realizing steady and high production of alumina and enhancing the competitive power of enterprises.On the background of production process of alumina in Henan Brach China Aluminium, this paper mainly does research in the establishment and application of intelligent integrated prediction model of RSA and LR. Firstly, the key factors that influence RSA and LR are acquired by analyzing the mechanism of process of HPD, then mechanism model of RSA and LR is established. Secondly, in order to compensate errors of mechanism model, multiple neural networks based on principle component analysis is put forward, thereby integrated model of mechanism model and neural network is proposed. Thirdly, matching model with self-tuning sample library based on cluster analysis is put forward. Finally, on the base of analyzing merits and flaws of integrated model of mechanism model and neural network and matching model, intelligent coordinator based on expert knowledge and statistics is designed to harmonize outputs of these two models, therefore intelligent integrated prediction model of RSA and LR is established.An real-world application in Henan Brach China Aluminium shows that intelligent integrated model is effective and it can predict RSA and LR on line very precisely.