Optimal Heating in Heat-Treatment Process Based on Grey Asynchronous Particle Swarm Optimization
LI Jia-dong1,LI Yong1,ZHAO Da-dong2,FU Tian-liang1,WANG Zhao-dong1,WANG Guo-dong1
1. State Key Laboratory of Rolling and Automation, Northeastern University, Shenyang 110004,Liaoning, China 2. School of Materials and Metallurgy, University of Science and Technology of Liaoning, Anshan 114051, Liaoning, China
Optimal Heating in Heat-Treatment Process Based on Grey Asynchronous Particle Swarm Optimization
LI Jia-dong1,LI Yong1,ZHAO Da-dong2,FU Tian-liang1,WANG Zhao-dong1,WANG Guo-dong1
1. State Key Laboratory of Rolling and Automation, Northeastern University, Shenyang 110004,Liaoning, China 2. School of Materials and Metallurgy, University of Science and Technology of Liaoning, Anshan 114051, Liaoning, China
ժҪ To ensure plate heating quality and reduce energy consumption in heat-treatment process, optimal heating for plates in a roller hearth furnace was investigated and a new strategy for heating procedure optimization was developed. During solving process, plate temperature forecast model based on heat transfer mechanics was established to calculate plate temperature with the assumed heating procedure. In addition, multi-objective feature of optimal heating was analyzed. And the method, which is composed of asynchronous particle swarm optimization and grey relational analysis, was adopted for solving the multi-objective problem. The developed strategy for optimizing heating has been applied to the mass production. The result indicates that the absolute plate discharging temperature deviation between measured value and target value does not exceed �� 8 ��, and the relative deviation is less than �� 0. 77%.
Abstract��To ensure plate heating quality and reduce energy consumption in heat-treatment process, optimal heating for plates in a roller hearth furnace was investigated and a new strategy for heating procedure optimization was developed. During solving process, plate temperature forecast model based on heat transfer mechanics was established to calculate plate temperature with the assumed heating procedure. In addition, multi-objective feature of optimal heating was analyzed. And the method, which is composed of asynchronous particle swarm optimization and grey relational analysis, was adopted for solving the multi-objective problem. The developed strategy for optimizing heating has been applied to the mass production. The result indicates that the absolute plate discharging temperature deviation between measured value and target value does not exceed �� 8 ��, and the relative deviation is less than �� 0. 77%.
LI Jia-dong,LI Yong,ZHAO Da-dong,FU Tian-liang,WANG Zhao-dong,WANG Guo-dong. Optimal Heating in Heat-Treatment Process Based on Grey Asynchronous Particle Swarm Optimization[J]. �й������ڿ���, 2012, 19(12): 1-7.
LI Jia-dong,LI Yong,ZHAO Da-dong,FU Tian-liang,WANG Zhao-dong,WANG Guo-dong. Optimal Heating in Heat-Treatment Process Based on Grey Asynchronous Particle Swarm Optimization. Chinese Journal of Iron and Steel, 2012, 19(12): 1-7.
2012, Vol. 19 
