Open AccessTemperature field modeling of the plate during hot rolling based on inverse heat conduction problem
Author(s) -
Wenhong Liu,
Siying Guo,
Siyu Zhang
Publication year - 2019
Publication title -
journal of physics. conference series
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.21
H-Index - 85
eISSN - 1742-6596
pISSN - 1742-6588
DOI - 10.1088/1742-6596/1300/1/012017
Subject(s) - particle swarm optimization , simulated annealing , inverse , thermal conduction , heat transfer , algorithm , field (mathematics) , heat transfer coefficient , mathematical optimization , mathematics , computer science , mechanics , thermodynamics , physics , geometry , pure mathematics
In the established temperature field model of plate hot rolling process, the heat transfer coefficients of each stage are solved by empirical formula, but due to the complexity of the production environment, temperature field models tend to be less accurate. In order to solve this problem, this paper designs a rolling experiment, collects the actual temperature data, and combines with genetic algorithm, simulated annealing algorithm and particle swarm optimization algorithm to correct the heat transfer coefficients of air-cooling zone, and the three algorithms are compared. Finally, the particle swarm algorithm is selected to establish the temperature field model of the hot rolling process. The average error of the final temperature field model calculation is within 14°C.