Simulation And Optimization Of Oxynitride Emissions During The Process Of Cement Precalcining Kiln

Cement is a kind of important raw material during the social production and construction,and it occupies indispensable status in people's life as a significant part of national economy.In the past decade,the cement production of China still keeps a high increasing rate.The demand of cement has the upside potential considering the current development of Chinese economy and the reserves of coal resources.With the continuous expansion of cement production and elimination of backward technology,the use rate of NSP kiln technology is growing.When the efficiency of energy is improving,the emission of NOx also increases significantly,which leads to more serious environmental problems.Existing technologies for NOx emission reduction are equipment modification,catalytic reduction and parameters control.However,the parameters optimization method provides a cost-effective way to solve the increasingly strict standard because of the development of computer science technology.This paper established predictive model to forecast the cement precalcining kiln NOx emissions and optimization based on actual production data of a cement company.The main research content of this paper as follows:(1)Study on artificial neural network and genetic algorithm to set an ANN-GA model to predict and optimize the NOx according to the operating parameters,use the actual data of cement company to train the model and the effect of model is good.According to the test result,the relative error between the predicted values and the actual values is less than 2%,the correlation coefficient is 0.9902.The result shows that the accuracy of the model is excellent to make accurate prediction of the NOx emission.GA is used to get the optimize parameters of production to realize reduction.The optimization of NOx emission is 165.9 mg/m3,which is less than the national standard 400 mg/m3.In addition,to make sure the effect that different parameters have on the NOx emission,the sensitivity analysis is analyzed.The result shows that the furnace temperature,raw material quantity and third air temperature have a great influence on the emission of NOx.(2)Study on multivariate linear regression model to establish the regression equation to predict and optimize the NOx emission under the same conditions.Optimize the regression model by stepwise considering the collinearity problem existing in the model.The test result of model shows that the relative error between the predicted values and the actual values is less than 4%m the correlation coefficient is 0.9176.The regression equation explains that the raw material quantity,third air temperature and coal quantity have a great effect on the emission of NOx.(3)Compare the ANN-GA model and multivariate linear regression from the prediction accuracy and model optimization,the result shows that the ANN-GA model has better effect.This paper uses the method of parameters optimization to predict and optimize the NOx emission of cement predecomposition kiln.Two normal models are set and compared.This paper could help the administer of cement company to get some support for decision-making on the reduction of NOx emission.