Research On Optimized Combustion Control Based On Fuzzy Neural Network Decomposition Furnace

As the core equipment of precalciner kiln,the main function is to bear the task of calcium carbonate decomposition in clinker calcination process,which can not only reduce the length and working load of rotary kiln,but also can effectively guarantee the stable operation of cement production line.The temperature of its decomposition furnace is directly related to the quality of cement clinker,too low clinker quality decline,too high energy waste.As the current domestic cement plant control most of the use of manual control,but also often only control the amount of coal and ignore the air volume,resulting in large energy consumption,temperature fluctuations,poor quality clinker and other issues.In order to solve these problems,this paper takes the cement ice clinker automatic control system production line of 4#cement line in Guangxi as the research background,adopts the control method of fuzzy neural network,controls the coal and wind to give the optimal design of the combustion control and software development.Which is of great significance to the normal production,energy saving and pollution reduction of cement clinker.The main work of this paper research results:1.Firstly,the basic working principle of the decomposition furnace is introduced,and the factors influencing the temperature of the decomposition furnace and the dynamic temperature model of the decomposition furnace are analyzed.The model is difficult to be confirmed.Based on the LS-SVM method,the outlet temperature model of the decomposition furnace is established and simulated and verified.The experimental results show that the accuracy of the model meets the requirements.2.By analyzing the difficulty of controlling the decomposition furnace and the influence of temperature analysis,the traditional control method is very difficult to control the decomposition furnace,and the intelligent control method is used to control the temperature of the decomposition furnace.The basic theory of fuzzy neural network is introduced,and the design of T-S fuzzy neural network controller is studied.The combustion controller based on T-S fuzzy neural network is designed and simulated.The simulation results show that the T-S fuzzy neural network controller has the advantages of small scheduling,strong robustness and self-learning ability.3.Based on the above-mentioned control strategy,the design and development of the optimized combustion control software for the decomposition furnace are completed.Its main modules include:user management,communication configuration,controller configuration,process monitoring,historical data management five functional modules.And through the OPC client and DCS(Wincc OPC server)to communicate.Industrial applications show that the temperature stability and reduce the oxygen content in the exhaust has a very good effect on the energy efficiency of enterprises and cement to play a very good effect for the enterprise to bring huge economic and environmental significance.