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Abstract:
Due to its synthetic and complex characters, the combustion process with fixed air-fuel ratio of shaft ore-roasting furnace is very difficult to he controlled stably, the fault is appeared frequently and lead to the combustion efficiency laigh. To deal with this problem, an intelligent control approach has been developed for the air-fuel ratio combination of case-based reasoning and neural network. The fault prediction model performs to predict the typical fault with the help of case-based reasoning technology is obtained with the working trend and the fault cases. According to these, the tuning value of air-fuel ratio are given by the algorithm based on neural network. The proposed method has been successfully applied to the combustion process of a shaft furnace, with increase of control accuracy for the combustion temperature, reduction of gas consumption and the fault ratios.
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Source :
Journal of Beijing University of Technology
ISSN: 0254-0037
Year: 2008
Issue: 3
Volume: 34
Page: 245-250
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SCOPUS Cited Count:
ESI Highly Cited Papers on the List: 0 Unfold All
WanFang Cited Count:
Chinese Cited Count:
30 Days PV: 8
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