摘要
为研究木粉与塑料共燃的氮氧化物生成规律,在自行设计的循环流化床装置上进行了二者的共燃实验。研究了温度、木粉和塑料粉混合比例对NO和NO2生成浓度的影响。实验结果表明:随温度升高,NO生成浓度升高,而NO2生成浓度迅速降低;随木粉和塑料粉混合比例增加,NO和NO2生成浓度均降低,且共燃时NO的生成量低于两种物料单独焚烧时其生成量的线性叠加。为寻找二者共燃时氮氧化物生成的一般性规律,采用BP神经网络建立了NO生成的预测模型,预测结果显示该模型具有很高的精度。
To study the law of NOx emissions from co-combustion of wood powder and plastic powder, the co-combustion experiments were performed in a CFB designed by ourselves. The influences of combustion temperature and the ratio of wood powder to plastic powder on the emission of NO and NO2 were focused. Experimental research showed that NO emissions increased with the temperature increasing, but NO2 emissions decreased rapidly with the temperature increasing; NO emissions and NO2 emissions decreased with the ratio of wood powder to plastic powder increasing, and the NO emissions were lower when co-combustion than the weighted arithmetic mean of NO emissions when these two fuels combusted respectively. In order to search the general law for NOx emissions from co-combustion of wood powder and plastic powder, a forecasting model of NO emissions based on back-propagation neural network was set up and the forecasted results showed that this model was very accurate.
出处
《电站系统工程》
北大核心
2006年第1期8-10,共3页
Power System Engineering
基金
深圳市科技计划项目资助(200436)
关键词
木粉
塑料粉
共燃
循环流化床
BP神经网络
wood powder
plastic powder
co-combustion
circulating fluidized bed
back-propagation neural network
