The Research Of The Decarburization Of Heavy Rail Steel Billet Of U75V

Decarburization is the quality of hot-rolled steel rail order one of the indicators. The quality indicators of (43kg/m~75kg/m) hot rolling rail issued by the Ministry of Railways, stipulates the decarburized depth of rail-head must be less than 0.5mm. Heavy rail steel U75V has higher carbon content,there is strong tendency of decarburization in the heating process.In this paper, For the excessive decarburization layer problem of Steel factory production line of heavy rail steel in the production of heavy rail steel of U75V. Through field testing, experimental study, finite element simulation and neural network modeling approach combined with many different ways focuses on the heavy rail steel billet heating process. Analysis the influencing factors of decarburization and study the relationship between the depth of decarburization and factors. Main contents and conclusions are shown as follows:(1) The tracking test of the On-site and billet heating process, the results show that the heating process's heating-up temperature and time in the furnace can meet the temperature requirements of rolling production process. And it's better to keep soaking temperature of the lower part more 20℃than the top.(2) Billet heating experimental studied the relationship between the decarburization of steel and the heating temperature and time. The results show that the depth of decarburization of steel increases with the increase of heating time and the increase of heating temperature, the decarburization speed with the heating temperature increased markedly accelerated.(3)Within the furnace and billet heating process was simulated in the laboratory experiments. Through the analysis of experimental results, Protective coating on the impact of decarburization, The use of coatings to reduce oxidation loss of 20% to 30%, the average reduction of 29.7% of the depth of decarburization; Optimized the billet heating process .(4) Using the ABAQUS finite element software for the numerical simulation of the billet heating process. The results of the optimization of billet heating process in order to reduce energy consumption and reduce the depth of decarburization played a certain role in guiding reference.(5) Using artificial neural network technology to establish a decarburization depth forecasting model of heavy rail. The model can be used for the real-time control of the heating furnace parameters, in order to prevent excessive decarburization depth of heavy rail.