An Integrated Optimal Control System For Aluminum Hydroxide Gas Suspension Calcinations

At present,the scale of China's alumina industry is developing rapidly and the productivity of alumina has been up to nineteen million tons per year.In order to achieve energy saving and emission reduction, it is imperative to carry out technological innovation.In the roasting procedure that affects the quality,yield and energy consumption,the gas suspension calcination process(G.S.C) which stands for the main developing trend in the fluidized calcinations has been widely adopted. Many applications indicate that it still has much improving space in the equipment configuration,manual adjustments and process control for the G.S.C.The optimization studies of equipment,operation and control can improve production and reduce energy consumption.This dissertation is supported by the National Natural Science Foundation of China and subjected in G.S.C with the productivity of fifty thousand tons per year,in which an integrated optimization strategy combining FLUENT,artificial neural networks,genetic optimization, fuzzy control and expert system technology is presented for equipment, operation and control optimization.The original research achievements of this paper are listed as follows:(1)In order to solve the problem of the scarcity in configuration information for combustion system,a three-dimension G.S.C model is studied by using a CFD software FLUENT.The obtained optimal results include:For a certain fuel,the optimal ratio of air to fuel(A/F) and optimal operation condition for low oxygen complete combustion are obtained;The optimal feeding inlet position is on partâ…£and optimal fixing position of V08 igniter is on partâ…¡of G.S.C;By setting the ratio of V08 to V19,NO emission declines; With increased preheated air temperature,considerable energy can be saved.The quantity of NO_x,CO and CO₂ emission estimated through simulation can serve as a very good reference to the production.(2)As the operation of cyclone separator is not fully explored,a three-dimensional P01 Grid model obtained by hexahedral approach in Gambit was applied in the simulation.With Reynolds stress turbulent viscous model,the physical field distributions and the particle tracks were computed through the gas phase coupled with the discrete phase.The separation efficiency in different inlet winds velocity,operation temperature,air leakage rate and physical structure are obtained and the reconstruct of P01 adopted circumfluent cyclone separator and certain dust collection equipments are discussed,which provides important reference for the optimization of operation.(3)In order to extend the existing process description modes,artificial neural networks(ANN),genetic algorithms and grey theory model(GM) were adopted to optimize G.S.C modeling.A temperature combinatorial optimal prediction model,emission soft measurement model and productivity estimation model are obtained. The temperature model was established based on GM(1,1) and ANN. The forecast accuracy of combinatorial model is over 90%as the absolute error±5℃is adopted,which meets the requirements of production adjustment.The structure of emission soft measurement model is ANN{3-5-4} and its forecast accuracy is 88.6%as the absolute error less than 1 is adopted.The prediction of new operation conditions deduced by the emission ANN model based on FLUNET simulation results can be taken as secondary simulation.The productivity estimation model is ANN{3-9-1} and its forecast accuracy is 96%as the relative error less than 1 is adopted,which is more advanced in process expression than the existing regression model.(4)To improve the conventional PID control,a roasting process fuzzy-expert control system was established.A Complex-PID controller and an expert regulator for A/F are designed.The Complex-PID controller is composed of fuzzy neural network(FNN), PID and threshold switch unit,by which the optimal or suboptimal control parameters can be obtained with fuzzy rules,neural networks and genetic algorithms.With the expert regulator for A/F,the optimal A/F value can be deduced by combining numerical simulation results, image analysis and oxygen content feedback information.A set of roasting process subsection adjustment control strategy is presented to achieve various conditions optimization,of which temperature error is within±5℃so as to create stable furnace conditions.(5)In order to extend the existing production and management modes,a roasting process guidance system based on ANNES was built.In this system,the explicit information is expressed by production rules and the implicit information by ANN model.And the transform between the two kinds of information is achieved by Membership function.A fault information base for centrifugal blower and Roots blower and a state regulation information base for combustion and process analysis are established,to which process analysis and monitoring can be achieved.A GA-ANNES optimization model was built to achieve energy analysis and to provide a good solution for higher yield with lower consumption.A guiding information base for cyclones separator operation is created and cyclones diagnosis and analysis are performed by ANNES.(6)A calcination SCADA system based on PLC and an integrated optimization system based on VC++ and Matlab are developed.The communications between the two systems were performed by three kinds of modes:OPC technology,consumer defined protocol and DeviceNet Bus.The PLC system performs as basic control and optimization system integrated neural networks,genetic algorithms and expert knowledge achieves process control and optimization.In this paper,the integrated optimal control system has been applied in G.S.C with the productivity of fifty thousand tons per year and the industrial tests have achieved satisfactory results:the heat consumption ups to 3.09MJ/kg,a decrease of 14.3%;the furnace temperature is controlled within 1040±5℃,a decrease of 8.8%;oxygen content is controlled within 1-2%,a decrease of 75%;NO emission is around 53ppm,a decrease of 53.9%.