Sintering Flue Gas Desulfurization Intelligent Control Strategy And Industrial Application Of Sulphur Dioxide

The steel industry is the pillar industry of our country and the lifeblood of the national economic development. The production of iron and steel created tremendous wealth for the community, but at the same time, the process of steel production creates large amounts of exhaust gas. The flue gas generated in steel smelting is mainly from the sintering process, most of the sintering process equipped with a flue gas desulfurization system, but due to the presence of strong nonlinearity, large time delay and uncertain disturbance factors, the effect of control in the desulfurization process is not satisfactory, as a result, a serious air pollution was caused by sulfur dioxide emissions, and threat to human survival environment. Therefore, the study of stability control in sintering flue gas desulfurization process is of great significance.This thesis considered the problems of nonlinearity, large time delay and disturbance in sintering flue gas desulfurization process, researched the intelligent control strategy of sintering flue gas desulfurization, established the desulfurization process sulfur dioxide concentration prediction model, and designed the optimal control strategy for the sulfur dioxide concentration. Simultaneously this thesis also researched the intelligent control method of the particle concentration, based on methods of soft measurement of the particle concentration in the circulating fluidized bed tower, whitch could increase the removal efficiency of sulfur dioxide, and control the amount of sulfur dioxide emissions. The research work of this thesis mainly focused on the following aspects.First, according to the characteristics of sintering flue gas desulfurization process, on the basis of the mechanism analysis of desulfurization process, combined with the mathematical modeling of discrete system and model identification methods, established the sulfur dioxide concentration prediction model. Second, predicted the value of sulfur dioxide concentration through the model, established an optimization objective of flue gas desulfurization process, and calculated the optimal value of the control variable using the optimization algorithm based on least square, and then proposed the optimal control strategy for sulfur dioxide concentration. Finally, considering the important influence of the particle concentration of material in desulfurization tower on the desulfurization process, researched the intelligent control method of the particle concentration, built the soft measurement model of the particle concentration combined with methods in fluid dynamics theory, and designed the fuzzy adaptive control method to control the particle concentration, ensuring conditions of removing sulfur dioxide reaction.The simulation verified the effectiveness of the proposed modeling and control methods. Further in order to verify the effect of the actual application, the development of sintering flue gas desulfurization optimal control system, based on the sintering plant in a large steel enterprise, is introduced in this thesis. The practical application results show that the system realized the control of sulfur dioxide concentration, improved the degree of automation of sintering flue gas desulfurization system, stabilized the sulfur dioxide concentration at the outlet of desulfurization system and effectively promoted the process of desulfurization reaction in the desulfurization tower, finally achieved the purpose of reducing sulfur dioxide emission.