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Combustion efficiency optimization and virtual testing: A data-mining approach
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DOI：10.1109/TII.2006.873598.png)
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Abstract
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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.
Keywords:
combustion efficiency
data mining
nonstationary process
process control
temporal data mining
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