The Research On Optimization Of Industrial Furnace Combustion Control Based On Fuzzy Neural Network

Cement decomposing furnace is the key equipment in cement production line,Decomposing Furnace,in some way,reflects a country's industrial and technical level.The critical factors affecting the temperature of decomposing furnace is as follows:(1)the kiln feed amount on the influence of coal temperature;(2)effect on the temperature of the raw material into the furnace;(3)three times the wind effect on the temperature;(4)effect of tail coal pressure on temperature;(5)raw material the influence of composition on temperature.The process of decomposition of cement raw material in decomposition furnace,is a quite complex lag,multi variable,multi disturbance and nonlinear process,so the decomposition crucible system modeling and control is difficult.Cement burning process is a multi parameter,strong interference resistance,large time-delay system,the neural network has self-learning and parallel processing ability,and fuzzy logic can be used to control the model of the unknown or imprecise.The control algorithm of fuzzy neural network which is applied to the combustion control of the furnace is feasible.And the optimization of the combustion control system does not produce pollution,and also can greatly reduce the emissions of waste gas.Therefore,the project has significant economic benefits,also has a very high-valued social benefits.Based on the background of the actual production of cement industry,analyzes the core technology in cement production and the key equipment which must ensure efficient raw meal decomposition rate;analysis of the domestic and international situation and development trend of combustion control,existing control method mainly adopts PID control,and the coal flow and the air-fuel ratio is set manually,operation isn't skilled and unpredictable fluctuations in operating conditions lead to poor control effect;on this basis,according to the characteristics of decomposition furnace combustion system,introduced the neural network fuzzy control,their advantages and disadvantages,and use the advantages of both the fuzzy control and neural network combination,proposes a fuzzy control algorithm of combustion optimization based on neural network,based on a large number of data analysis to obtain the fuzzy control rules of learning,to realize the optimization of the combustion control of precalciner;In MATLAB simulation software,experimentalresults show that the control method based on fuzzy neural network can meet the control requirements;in the actual industrial operation,through the fuzzy neural network system and flue gas analyzer control parameters set high temperature fan kiln adjustment range,regulating range,rotary kiln coal regulating range,adjust the speed of grate cooler range and cooler motor current adjustment range,and set the temperature of decomposing furnace,kiln head temperature and kiln temperature.In order to improve the decomposition rate of clinker,enhance the grade of cement,to reduce the consumption of energy,bring economic benefits and the final value for the enterprise in the actual production.