【摘要】 为提高选择性催化还原(SCR)脱硝系统的控制品质与经济性,需要建立精确的SCR脱硝反应器入口NO_x生成量动态模型。本文基于模糊树模型建立了SCR反应器入口NO_x生成量动态模型,提出采用复相关系数的时滞联合估计方法,对影响NO_x生成量的模型输入变量进行时滞估计。将该方法应用于某600 MW燃煤机组的运行数据,并对输入变量采用相关系数法和复相关系数法进行时滞估计对比。结果表明:模糊树模型的建模精度较高、泛化能力强;在模型输入变量进行时滞估计时,相较于相关系数法,采用复相关系数法对模型精度和泛化能力提升程度更高。更多还原

【Abstract】 In order to improve the control quality and economy of selective catalytic reduction(SCR) denitration system, it is necessary to establish an accurate dynamic model of NO_x production at inlet of the SCR denitrification reactor. On the basis of fuzzy tree model, this paper builds up a dynamic model for NO_x production at the SCR reactor inlet, and proposes using a joint time-delay estimation method based on multiple correlation coefficients to estimate the time-delay of the input variables which affect the NO_x production. The method was applied to the operation data of a 600 MW coal-fired unit, and the time-delay of input variables were estimated by correlation coefficient method and multiple correlation coefficient method. The experimental results show that,the fuzzy-tree model has high accuracy and generalization ability, the time-delay estimation of input variables based on multiple correlation coefficient method improves more accurate and generalization ability for the model than the correlation coefficient method.更多还原