| In China,coal is an important chemical energy source widely used in industry and daily life.However,the combustion of coal generates a large amount of nitrogen oxides,which is one of the main causes of air pollution.Nitrogen oxides not only cause environmental problems such as acid rain and greenhouse effect,but also pose a serious threat to human health.To address this issue,current methods in my country involve optimizing burner structures,employing air classification technology,and reducing catalysts to minimize NO_x emissions.However,with the rapid advancement of science and technology,there is increasing focus on using intelligent algorithms to predict NO_x emissions.Such predictions can help businesses evaluate whether their combustion equipment meets national standards and take necessary measures to protect the environment and human health.This paper seeks to contribute to the goal of achieving low-nitrogen combustion by exploring burner structure optimization and establishing a NO_x prediction model.Firstly,this paper investigates the research status of low-nitrogen combustion and NO_x prediction at home and abroad,and analyzes the formation mechanism of NO_x and the pyrolysis process of pulverized coal,so as to take further measures to optimize the structure of the burner and reduce the emission of nitrogen oxides.Secondly,this paper introduces the structure and working principle of the self-sustaining burner adopted in detail.This burner uses the reducing gas produced by the self-sustaining combustion of pulverized coal inside the burner to reduce the NO_x produced during the combustion process of the boiler.Thereby achieving low NO_x combustion.In the research process of this paper,the 40 MW L-shaped coal-fired boiler was taken as the research object and simulated and analyzed.Due to the complex chemical reaction of pulverized coal combustion,the internal reaction mechanism cannot be intuitively understood.The reaction mechanism of the whole process of entering the furnace combustion is studied.The best model suitable for this paper is selected by rationally selecting the governing equations and calculation models used in numerical simulation.Then,mesh the boiler model,set boundary conditions,and verify the reliability of the model.By analyzing the distribution of the velocity field and temperature field inside the furnace under the basic working conditions,it is found that the temperature distribution in the furnace during the boiler combustion process has an important impact on the air staged combustion and the control and optimization of subsequent thermal parameters.On the basis of the simulation,the boiler gas phase velocity,the proportion of secondary air and overfired air,and the position of overfired air are optimized and adjusted to find the optimal working condition for stable and low NO_x combustion of the boiler.Finally,in order to visualize the simulation results and reduce the long simulation calculation time,this paper takes the simulation results under the optimal working conditions as the data set of the NO_x prediction model and performs data preprocessing on the data set.In this paper,LSSVM is selected as the prediction model,which has high computational efficiency and good generalization ability.In order to further improve the predictive ability of the algorithm,this paper improves the traditional Whale Optimization Algorithm(WOA),and compares the improved algorithm with other algorithms.The results show that the improved WOA algorithm has better optimization ability and convergence speed.The improved WOA algorithm is applied to the NO_x prediction model,and the prediction effect of the model is analyzed.It is found that the prediction results of the model can be used as an important basis for the optimization and adjustment of boiler combustion parameters,which will improve the real-time prediction and adjustment of boiler NO_x emissions.Environmental pollution is of great significance. |
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