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Soft-Sensing Method for Optimizing Combustion Efficiency of Reheating Furnaces

Wang, JG, Shen, T, Zhao, JH, Ma, SW, Wang, XF, Yao, Y and Chen, T (2016) Soft-Sensing Method for Optimizing Combustion Efficiency of Reheating Furnaces Journal of the Taiwan Institute of Chemical Engineers.

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Abstract

Rolling mill reheating furnaces are widely used in large-scale iron and steel plants, the efficient operation of which has been hampered by the complexity of the combustion mechanism. In this paper, a soft-sensing method is developed for modeling and predicting combustion efficiency since it cannot be measured directly. Statistical methods are utilized to ascertain the significance of the proposed derived variables for the combustion efficiency modeling. By employing the nonnegative garrote variable selection procedure, an adaptive scheme for combustion efficiency modeling and adjustment is proposed and virtually implemented on a rolling mill reheating furnace. The results show that significant energy saving can be achieved when the furnace is operated with the proposed model-based optimization strategy.

Item Type: Article
Subjects : Chemical and Process Engineering
Divisions : Faculty of Engineering and Physical Sciences > Chemical and Process Engineering
Authors :
NameEmailORCID
Wang, JGUNSPECIFIEDUNSPECIFIED
Shen, TUNSPECIFIEDUNSPECIFIED
Zhao, JHUNSPECIFIEDUNSPECIFIED
Ma, SWUNSPECIFIEDUNSPECIFIED
Wang, XFUNSPECIFIEDUNSPECIFIED
Yao, YUNSPECIFIEDUNSPECIFIED
Chen, TUNSPECIFIEDUNSPECIFIED
Date : 20 October 2016
Identification Number : 10.1016/j.jtice.2016.09.037
Copyright Disclaimer : © 2016. This manuscript version is made available under the CC-BY-NC-ND 4.0 license http://creativecommons.org/licenses/by-nc-nd/4.0/
Depositing User : Symplectic Elements
Date Deposited : 24 Oct 2016 14:58
Last Modified : 20 Oct 2017 02:08
URI: http://epubs.surrey.ac.uk/id/eprint/812574

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