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影响燃煤锅炉氮氧化物生成的因素很多且规律复杂。利用人工神经网络技术,使用某一电厂低NOX排放燃烧优化试验的数据,建立了该锅炉氮氧化物的排放模型。该模型预测精度较高、结果可信。通过建立的神经网络模型分析了配风方式的影响。结果表明:缩腰型配风方式较佳,而倒宝塔型配风方式优于正宝塔型配风方式。建立的神经网络模型可以为燃煤锅炉通过优化燃烧降低NOX排放提供理论指导。
There are many factors affecting the formation of nitrogen oxides in coal-fired boilers and their laws are complicated. Using artificial neural network technology, using the data of a low NOx emission combustion optimization test of a power plant, the nitrogen oxide emission model of the boiler was established. The model has higher prediction accuracy and credible results. The effect of the air distribution mode is analyzed through the established neural network model. The results show that the method of reducing waist type is better, and the inverted pagoda type air distribution method is better than the positive pagoda type air distribution method. The established neural network model can provide theoretical guidance for coal-fired boilers to reduce NO x emission through optimizing combustion.