NOx content prediction based on principal component analysis and multivariable process monitoring

ZHAO Zhihong; HAN Chao; ZHAO Wenjie

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NOx content prediction based on principal component analysis and multivariable process monitoring

Thermal Power Generation Issue 6, (2016)

更新时间：2025-09-28

- NOx content prediction based on principal component analysis and multivariable process monitoring
- 作者机构：
  
  1. 内蒙古京隆发电有限责任公司，内蒙古丰镇,012100
  2. 华北电力大学控制与计算机工程学院,河北,保定,071003
- 作者简介：
- 基金信息：
- DOI：
  CLC： TK39
- Published Online：15 July 2016，
  
  Published：2016
- 稿件说明：
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ZHAO Zhihong, HAN Chao, ZHAO Wenjie. NOx content prediction based on principal component analysis and multivariable process monitoring[J]. Thermal Power Generation, 2016, (6).
DOI：

ZHAO Zhihong, HAN Chao, ZHAO Wenjie. NOx content prediction based on principal component analysis and multivariable process monitoring[J]. Thermal Power Generation, 2016, (6). DOI：

摘要

针对火电厂烟气NOx质量浓度检测分析仪存在延时较长的问题

本文首先采用主元分析及多变量过程监测选出影响脱硝反应器入口烟气NOx质量浓度的主导因素

再根据分析仪的大致延时时间Ts

选取Ts后反应器入口烟气NOx质量浓度数据为训练信号

进而利用最小二乘支持向量机(LS-SVM)建立反应器入口烟气NOx质量浓度的预测模型。采用某电厂历史运行数据对该预测模型进行训练及测试

结果表明:利用主元分析及多变量过程监测方法从多个辅助变量中选出主导因素

简化模型结构的同时也使预测模型具有较好的学习及泛化能力。该方法是反应器入口烟气NOx质量浓度准确、实时预测的一种可行方法。

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