Two Soft-sensing Methods of Ultra-supercritical Once-through Boiler Water-coal Ratio

被引：0

作者：

Zhang Wei ^{[1
]}

Liu Ji-Zhen ^{[1
]}

Qin Tian-Mu ^{[1
]}

Li Yi-Xin ^{[2
]}

机构：

[1] North China Elect Power Univ, State Key Lab Alternate Elect Power Syst Renewabl, Beijing 102206, Peoples R China

[2] China Power Engn Consulting Grp, North China Power Engn Co Ltd, Being 100011, Peoples R China

来源：

PROCEEDINGS OF THE 35TH CHINESE CONTROL CONFERENCE 2016 | 2016年

关键词：

Ultra-supercritical once-through boiler; water-coal ratio; soft measurement; time series; principal component regression;

D O I：

暂无

中图分类号：

TP [自动化技术、计算机技术];

学科分类号：

0812 ;

摘要：

Taking a 1000MW ultra-supercritical once-through boiler as an example for research, two kinds of soft measurement methods of once-through boiler water-coal ratio is studied: With Auto Regressive Integrated Moving Average (ARIMA) time series method, water-coal ratio data after filtering is processed with parameter estimation and dynamic prediction, then the error analysis verified the model can accurately predict water-coal ratio; By analyzing several procedure variables which are involved with water-coal ratio and applying the method of principal component regression, a prediction measurement about water-coal ratio was formed. The two methods respectively used time series analysis and principal component regression to calculate and predict water-coal ratio, and results proved that the two soft-measuring methods can to some extent overcome the large delay and big error which are the characteristics of traditional monitoring methods.

引用

页码：1915 / 1920

页数：6

共 27 条

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