摘要
为了降低锅炉污染烟气和残渣的排放,实现节能减排,提出一种基于模糊神经网络控制的锅炉超低排放控制方法。构建锅炉超低排放的控制约束参量模型,以锅炉凝渣量、炉膛温度、压力、锅炉热效率等参量为约束指标,构建一个多元控制目标函数。采用模糊神经网络结构模型对输入的控制参量模型进行自适应寻优,结合模糊控制规则实现锅炉排放过程的优化控制,实现超低排放。仿真结果表明,采用该方法锅炉排放过程,能降低锅炉燃烧污染物的排放量,控制过程收敛性和品质较好。
In order to reduce the pollution of boiler flue gas and residue emissions, achieve energy - saving emission reduction, the need for research of ultra low emission control method of boiler, a boiler based on fuzzy neural network control of ultra low emission control method. The construction control parameter model of ultra low emission boiler, the boiler condensate slag, furnace temperature and pressure. The thermal efficiency of the boiler parameters such as constraint index, construct a multivariate control objective function. By using the fuzzy neural network control structure model parameter model of the input adaptive optimization, combination optimization of boiler emissions control in the process of fuzzy control rules, to achieve ultra low emission. The simulation results show that using the method of boiler emissions can process. Reduce the boiler combustion emissions of pollutants, control the process of convergence and better quality.
出处
《环境科学与管理》
CAS
2017年第5期115-118,共4页
Environmental Science and Management
