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山东大学学报(工学版) ›› 2010, Vol. 40 ›› Issue (1): 126-128.

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锅炉氮氧化物排放量检测中PLS的应用改进

董增寿 刘明君   

  1. 太原科技大学电子信息工程学院, 太原 山西 030024
  • 收稿日期:2009-02-10 出版日期:2010-02-16 发布日期:2009-02-10
  • 作者简介:董增寿(1970-),男,山西寿阳人,副教授,硕士研究生,主要研究方向为遥感图像,图像处理.E-mail:ansondon@sohu.com
  • 基金资助:

    山西省自然科学基金资助项目(2007011048)

The application improvement of PLS in  boiler NOx  emissions testing

  1. School of Electronic and Information Engineering, Taiyuan University of Science and Technology, Taiyuan  030024, China
  • Received:2009-02-10 Online:2010-02-16 Published:2009-02-10

摘要:

通过确定与氮氧化物生成量密切相关的锅炉运行参数,利用改进的偏最小二乘法(partial least squares, PLS)计算模型对锅炉煤燃烧过程中氮氧化物排放量进行预测。PLS的改进是在随机矩阵法均化校准模型基础上,结合影响氮氧化物排放量的各个因素以及排放量中氮含量的单变量输出,对PLS模型改进。利用PLS改进的计算模型对氮氧化物排放量进行预测,并同实测值进行对比,结果表明:该方法对预测氮氧化物排放量的准确度和计算速度较常规的PLS均有较大提高。该方法为实现数据采集程序计算一体化提供了一种手段。

关键词: 偏最小二乘法;随机矩阵;模型;氮氧化物

Abstract:

By identifying  boiler operating parameters  closely related to  nitrogen oxides emissions, the improvement of PLS was used to predictthe nitrogen oxides emissions in the boiler coal combustion process. Based on calibration models uniformed by the random matrix and combined with several factors influenced by nitrogen oxides emissions, and variable single-output of the emissionsof nitrogen content, the PLS model was improved. The improved calculation modelwas used to test nitrogen oxides emissions. The result showed that this method was more accurate and faster than  conventional PLS when used to predict the emission of  nitrogen oxides. This method could  provide a means for the integration of  data calculation and process collection.

Key words: partial least squares(PLS); random matrix; model; nitrogenoxides

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