Modeling Of Electrical Smelting Furnace For Magnesia Smelting Process

Energy conservation is one of the trends of modern industrial development. Improving energy efficiency accords with the long-term interests of human development. However, limited to the current technical conditions, a number of industrial processes are essential to high pollution and high energy consumption, forcing people to study and improve the industrial processes.Electrical-smelted magnesia is a sort of sophisticated fireproof material which has the properties of high temperature resistibility and dense structure. It is an important material. The objective of this research is the production of electrical-smelted magnesia. It is widely used in metallurgy and aerospace industry and other fields. The three-phase AC electrical smelting furnace for magnesia (ESFM) is an important equipment for producing the electrical-smelted magnesia. It belongs to a kind of mine hot electric arc furnace. The magnesite powder and light-burning magnesium powder are heated by the furnace charge resistance and the electrodes arc, this is a high energy consumption process. In addition, the process has features such as time-varying, multivariable, strong coupling.Facing the problems, researches include the following related parts in this thesis:(1) The physical and chemical changes of furnace in normal operating conditions are researched. And the principle of heat transfer between material batches in ESFM is analyzed deeply in this thesis;(2) According to thermal principle and the actual site conditions, a current set approach is proposed through heat transfer calculating, which can conserve the energy. And the value of the consuming energy can be gottern;(3) Combining PLS and iterative learning control (ILC), adding constraints, and then using particle swarm optimization (PSO) to tracke the set-point value. And the simulation results show that the algorithm is effective.