Combustion efficiency optimization and virtual testing: A data-mining approach

被引：62

作者：

Kusiak, Andrew ^{[1
]}

Song, Zhe ^{[1
]}

机构：

[1] Univ Iowa, Dept Mech & Ind Engn, Integrated Syst Lab, Iowa City, IA 52242 USA

来源：

IEEE TRANSACTIONS ON INDUSTRIAL INFORMATICS | 2006年 / 2卷 / 03期

关键词：

combustion efficiency; data mining; nonstationary process; process control; temporal data mining;

D O I：

10.1109/TII.2006.873598

中图分类号：

TP [自动化技术、计算机技术];

学科分类号：

0812 ;

摘要：

In this paper, a data-mining approach is applied to optimize combustion efficiency of a coal-fired boiler. The combustion process is complex, nonlinear, and nonstationary. A virtual testing procedure is developed to validate the results produced by the optimization methods. The developed procedure quantifies improvements in the combustion efficiency without performing live testing, which is expensive and time consuming. The ideas introduced in this paper are illustrated with an industrial case study.

引用

页码：176 / 184

页数：9

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