Alumina Production Four-efficient Countercurrent Falling Film Evaporation Process Of Export Concentration Prediction Model Study

The practices of production indicated that, in the evaporation process of alumina production, the feed outlet concentration is an important indicator; it is also the primary base for regulating the operational parameters (flow of imported feed, the fresh steam flow and pressure). Because the manual measurement of the feed outlet concentration lag behind production process several hours later, it's difficult for us to modify the model by feedback timely. Further, owing to the artificial regulation to steam flow and other operating parameters, the adjustment of operating parameters for the control of outlet concentration is also built on the experience of the operators and the adjustment time of system is too long.In order to solve the problem of the outlet concentration forecast in the evaporation process and establish the relationship between outlet concentration and the operating parameters, the forecast model of the outlet concentration of the evaporation process is established by studying the four-effect back-feed falling film evaporation system of a certain alumina plant. This paper establishes a mechanism model based on materiel balance, heat balance and phase balance by analyzing the mechanism. Further, based on industrial running data, a BP neural network model for the forecast of the outlet concentration is established, whose inputs are the direct influencing factors of the outlet concentration and the output is the outlet concentration, too.The characters of the two models are analyzed respectively, and some conclusions can be drawn as follows: the BP neural network model's fitting performance is fine by and large, but it can not predict exactly when the work conditions are unstable because of the shortage of data; the mechanism model's precision is lower than the former generally, but its effect is better than it when the work conditions change abruptly. So an intelligent integrated forecast model is established by combination the two models above. Actual production application indicate that the intelligent integrated model could do estimation well in any condition and could provide reference to the optimization of the industrial operation in the evaporation process of alumina production.