文章基本信息

标题：Realization of BP neural network modeling based on NOXof CFB boiler in DCS
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作者：Jianyun Bai ; Zhujun Zhu ; Qi Wang 等
期刊名称：IOP Conference Series: Earth and Environmental Science
印刷版ISSN：1755-1307
电子版ISSN：1755-1315
出版年度：2018
卷号：121
期号：5
页码：052025
DOI：10.1088/1755-1315/121/5/052025
语种：English
出版社：IOP Publishing
摘要：In the CFB boiler installed with SNCR denitrification system, the mass concentration of NO _X is difficult to be predicted by the conventional mathematical model, and the step response mathematical model, obtained by using the step disturbance test of ammonia injection,is inaccurate. this paper presents two kinds of BP neural network model, according to the relationship between the generated mass concentration of NO _X and the load, the ratio of air to coal without using the SNCR system, as well as the relationship between the tested mass concentration of NO _X and the load, the ratio of air to coal and the amount of ammonia using the SNCR system. then itrealized the on-line prediction of the mass concentration of NO _X and the remaining mass concentration of NO _X after reductionreaction in DCS system. the practical results show that the average error per hour between generation and the prediction of the amount of NO _X mass concentration is within 10 mg/Nm³,the reducing reaction of measured and predicted hourly average error is within 2 mg/Nm³, all in error range, which provides a more accurate model for solvingthe problem on NO _X automatic control of SNCR system.