针对超超临界机组过热蒸汽系统模型辨识,采用基于数据驱动的闭环子空间辨识方法直接得到系统的阶跃响应系数,结合传统的SISO(Single Input Single Output)辨识方法,并利用最小二乘算法回归出系统的低阶传递函数模型.通过对某电厂超超临界机组过热蒸汽系统进行闭环辨识,结果表明,该策略很好地融合了子空间方法的简便性以及传统SISO辨识方法的最优性,并成功用于超超临界机组过热蒸汽系统模型辨识.
[目的]研究出厂水水质综合评价指数(finished drinking water quality index,FDWQI)能否综合反映上海市生活饮用水出厂水的实际情况。[方法]运用FDWQI对上海市13家市级水厂的出厂水水质卫生情况进行评价。[结果]以长江水为水源的水厂全年FDWQI平均值为20.19,每月的评价结果"优"、"良"各半,以黄浦江上游水为源水的水厂全年FDWQI平均值为24.25,每月的评价结果以"良"为主。FDWQI在春季波动较小,冬季变化差异大。[结论]FDWQI的结果与本市水质情况基本吻合,但其科学性、客观性还有待在今后实际应用中进一步验证。
A novel online process monitoring and fault diagnosis method of condenser based on kernel principle component analysis （KPCA） and Fisher discriminant analysis （FDA） is presented. The basic idea of this method is： First map data from the original space into high-dimensional feature space via nonlinear kernel function and then extract optimal feature vector and discriminant vector in feature space and calculate the Euclidean distance between feature vectors to perform process monitoring. Similar degree between the present discriminant vector and optimal discriminant vector of fault in historical dataset is used for diagnosis. The proposed method can effectively capture the nonlinear relationship among process variables. Simulating results of the turbo generator＇s fault data set prove that the proposed method is effective.
