TY - JOUR
T1 - Integrated Intelligence Control Based on Fuzzy and AI for Reheating Furnace
AU - Liao, Yingxin
AU - Wu, Min
AU - Hirota, Kaoru
AU - Dong, Fangyan
AU - Cao, Weihua
N1 - Publisher Copyright:
© Fuji Technology Press Ltd.
PY - 2005/3
Y1 - 2005/3
N2 - An integrated intelligence control method based on fuzzy and artificial intelligence (AI) is proposed aiming at combustion control of reheating furnace in steel rolling mill. Both fuzzy and AI strategies are used to solve problems of the bigger overshoot and the slower response in conventional hearth temperature control when gas pressure and heat value are frequently and acutely varied. The fuel-air ratio optimization and flux tracking modules based on AI respectively decrease fuel consumption and prolong the lifetime of actuators. The proposed method is implemented on an intelligence controller and distributed controllers, and the field test on two reheating furnaces in Lianyuan Iron and Steel Group Co. Ltd., Loudi, Hunan, China confirms that hearth temperature standard deviation, fuel consumption, and high temperature oxidation of billet are respectively decreased by 50%, 12%, and 10% over the current manual method. The proposed method delivers superior performance for reheating furnace in steel industry, but also it can be applied for other type furnaces in steel industry and in other industries, where further performance improvement might be achieved by adding a self-organizing capability to the fuzzy logic and AI control.
AB - An integrated intelligence control method based on fuzzy and artificial intelligence (AI) is proposed aiming at combustion control of reheating furnace in steel rolling mill. Both fuzzy and AI strategies are used to solve problems of the bigger overshoot and the slower response in conventional hearth temperature control when gas pressure and heat value are frequently and acutely varied. The fuel-air ratio optimization and flux tracking modules based on AI respectively decrease fuel consumption and prolong the lifetime of actuators. The proposed method is implemented on an intelligence controller and distributed controllers, and the field test on two reheating furnaces in Lianyuan Iron and Steel Group Co. Ltd., Loudi, Hunan, China confirms that hearth temperature standard deviation, fuel consumption, and high temperature oxidation of billet are respectively decreased by 50%, 12%, and 10% over the current manual method. The proposed method delivers superior performance for reheating furnace in steel industry, but also it can be applied for other type furnaces in steel industry and in other industries, where further performance improvement might be achieved by adding a self-organizing capability to the fuzzy logic and AI control.
KW - artificial intelligence
KW - fuzzy
KW - integrated intelligence control
KW - reheating furnace
UR - http://www.scopus.com/inward/record.url?scp=85167503415&partnerID=8YFLogxK
U2 - 10.20965/jaciii.2005.p0211
DO - 10.20965/jaciii.2005.p0211
M3 - Article
AN - SCOPUS:85167503415
SN - 1343-0130
VL - 9
SP - 211
EP - 222
JO - Journal of Advanced Computational Intelligence and Intelligent Informatics
JF - Journal of Advanced Computational Intelligence and Intelligent Informatics
IS - 2
ER -