[1]金秀章,郝兆平,佟纯涛,等.KPCA和LSSVM在SCR脱硝反应器入口NOx含量软测量中的应用[J].工业仪表与自动化装置,2016,(05):124-128.
　JIN Xiuzhang,HAO Zhaoping,TONG Chuntao,et al.The application of KPCA and LSSVM in the soft sensing of SCR denitration reactor inlet NOx content[J].Industrial Instrumentation & Automation,2016,(05):124-128.
点击复制

KPCA和LSSVM在SCR脱硝反应器入口NOx含量软测量中的应用(PDF)

《工业仪表与自动化装置》[ISSN:1000-0682/CN:61-1121/TH]

Title:: The application of KPCA and LSSVM in the soft sensing of SCR denitration reactor inlet NOx content

Author(s):: JIN Xiuzhang; HAO Zhaoping; TONG Chuntao; YIN Xiaojing; (School of Control and Computer, North China Electric Power University, Hebei Baoding 071003, China)

摘要:: SCR脱硝反应器入口NOx含量及时、准确地测量，对于精确调节喷氨量，控制NOx排放至关重要。针对NOx气体分析仪测量滞后的问题，提出了基于KPCA和LSSVM的软测量模型。根据某电厂采集的数据样本规模较大的情况，为了提高NOx软测量模型的精度，该文首先进行基于相似度函数的样本优选，减少样本冗余信息，简化样本模型。然后对于选取的与反应器入口NOx有关的18个辅助变量进行核主元分析(KPCA)，对样本进行特征提取，降低样本维数，以此作为最小二乘支持向量机(LSSVM)软测量模型的输入，提高软测量模型的精度，对

Abstract:: The timely, accurate measurement of SCR denitration reactor inlet NOx content is very important to accurately adjust the amount of ammonia spray and the NOx emission control. According to the serious delay of the NOx emission analyzer which used in the power plant, a soft-sensing based on Kernel Principal Component Analysis and Least Support Vector Machine is proposed. The original data is acquired from a certain power plant, and the sample size is very large. The KPCA method is not suitable for the analysis of a large number of samples. So firstly use the method of similarity function optimization to simplify the input samples and reduce the redundant information. In order to improve the timely, accuracy of NOx-content, 18 auxiliary parameters that connected to NOx were analyzed. The least square vector machine(LSSVM) with the kernel principal component analysis was used to analyze the related parameters and established the soft measurement model.

[1] 孙克勤,韩祥.燃煤电厂烟气脱硝设备及运行[M].北京:机械工业出版社,2011.

[2] 内蒙古电力科学研究院.SCR烟气脱硝技术及工程应用 [M].北京:中国电力出版社,2014.

[3] 俞金寿.软测量技术及其应用[J].自动化仪表,2008.

[4] 韩璞,乔弘,翟永杰,等.火电厂热工参数软测量技术的发展和现状[J].仪器仪表学报,2007,28(6):1139-1146.

[5] 黄勇.SCR烟气脱硝系统运行控制策略[J].电子科技, 2014(21):115 - 116.

[6] 陈荣超.燃煤电厂脱硝NOx的软测量技术和自动控制优化[J].电力科学与工程,2015, 31(1):15–19.

[7] 梁绍华,李秋白,黄磊,等.锅炉在线燃烧优化技术的开发及应用[J].动力工程,2008,28(1): 33–35,53.

[8] 王雅彬,李晓敏.基于支持向量机的电站锅炉NOx 排放软测量模型[J].电力科学与工程, 2012,28(4): 55–59.

[9] 陈庆文,马晓茜,刘翱.大型电站锅炉混煤掺烧的NOx排放特性预测与运行优化[J].中国电机工程学报,2009, 29(23): 20-26.?

[10] 张传标,倪建军,刘明华,等.样本优化核主元分析及其在水质监测中的应用[J].中国环境监测, 2012(02):

[11] 徐晔,杜文莉,钱锋.基于核主元分析和最小二乘支持向量机的软测量建模[J].系统仿真学报,2007,19(17): 3873-3875, 3918.

[12] 金秀章,韩超. KPCA-LSSVM在磨煤机一次风量预测中的应用[J].自动化仪表,2015, 36 (3): 62 -67.

备注/Memo:: 收稿日期：2015-04-18
作者简介：金秀章（1969），男，河北保定人，副教授，主要从事先进控制策略在大型电力机组的控制研究。E-mail: jinxzsys@163.com.

更新日期/Last Update: 1900-01-01