Bayer Process Caustic Ratio And Dissolution Rate Of The Prediction Model-based Ingredients Parameter Optimization Of The Set

The original ore pulp batching and the High-Pressure Digestion (HPD) are two important process in the alumina production. They connect and influence each other. The original ore pulp batching is the first process in the alumina production of method of Bayer ,which is in the purpose of making the qualified original ore pulp for the process of High-Pressure Digestion (HPD).The original ore pulp batching plays an important part in the production of alumina. Whether or not produce the original ore pulp which satisfies the produce demand directly affect Ratio of Soda to Alumina(RSA) and Leaching Rate(LR) which are two very important economical and technical indices in the process of High-Pressure Digestion (HPD) of alumina. But at present batching parameters are all operated and calculated by hand, and they do not show the change of on-the-spot craft situation of HPD , which cause RSA and LR unstably. They are unable to meet the real control request. So this text proposes one kind of technology on the basis of the prediction model of RSA and LR to optimize the batching parameters , which effectively settle the problem of batching parameters' optimization . The main research results include:(1) In this paper 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, multiple neural networks based on principle component analysis is put forward, thereby integrated model of mechanism model and neural network is proposed.(2) In this paper the key factors that influence L/S of the original ore pulp and the relation of them are acquired by analyzing the mechanism of process of batching, then the mechanism model of L/S is established by the balanced principle of the supplies. The composition parameters in the mechanism model use the grey model to predict, which have solved the problem that the parameter is measured lagging behind.(3) In order to solve the defect of the L/S mechanism model that it cannot show the change of on-the-spot craft situation, I excavate out thefuzzy expert's rule of RSA , LR and L/S from a large number of on-the-spot data of factory Using the theory of fuzzily distinguish by analyzing the mechanism of process of HPD, and revise the L/S mechanism model according to the prediction result of RSA and LR soft model.Simulation results show that we will optimize the L/S effectively using the intelligent integrated prediction model of RSA and LR and the production will be steady.