%0 Journal Article
%T Predicting Low NOx Combustion Property of a Coal-Fired Boiler<br>燃煤锅炉低氮氧化物燃烧特性的神经网络预报
%A Zhou Hao
%A Mao Jianbo
%A Chi Zuohe
%A Jiang Xiao
%A Wang Zhenhua
%A Cen kefa
%A <br>周昊
%A 茅建波
%A 池作和
%A 蒋啸
%A 王正华
%A 岑可法
%J 环境科学
%D 2002
%I 
%X More attention was paid to the low NOx combustion property of the high capacity tangential firing boiler, but the NOx emission and unburned carbon content in fly ash of coal burned boiler were complicated, they were affected by many factors, such as coal character, boiler's load, air distribution, boiler style, burner style, furnace temperature, excess air ratio, pulverized coal fineness and the uniformity of the air and coal distribution, etc. In this paper, the NOx emission property and unburned carbon content in fly ash of a 600MW utility tangentially firing coal burned boiler was experimentally investigated, and taking advantage of the nonlinear dynamics characteristics and self learning characteristics of artificial neural network, an artificial neural network model on low NOx combustion property of the high capacity boiler was developed and verified. The results illustrated that such a model can predicate the NOx emission concentration and unburned carbon content under various operating conditions, if combined with the optimization algorithm, the operator can find the best operation condition of the low NOx combustion.
%K utility boiler
%K NOx emission
%K unburned carbon content
%K artificial neural network<br>锅炉
%K NOx
%K 飞灰含碳量
%K 人工神经网络
%U http://www.alljournals.cn/get_abstract_url.aspx?pcid=3FF3ABA7486768130C3FF830376F43B398E0C97F0FF2DD53&cid=A7CA601309F5FED03C078BCE383971DC&jid=64CD0AA99DD39F69401C615B85F123EF&aid=7AF15DCB9029E0C6&yid=C3ACC247184A22C1&vid=EA389574707BDED3&iid=0B39A22176CE99FB&sid=13553B2D12F347E8&eid=BC12EA701C895178&journal_id=0250-3301&journal_name=环境科学&referenced_num=17&reference_num=2